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style="color:transparent" srcSet="/_next/image?url=https%3A%2F%2Fprod-discovery.edx-cdn.org%2Fcdn-cgi%2Fimage%2Fwidth%3Dauto%2Cheight%3Dauto%2Cquality%3D75%2Cformat%3Dwebp%2Fmedia%2Fcourse%2Fimage%2Fda1b2400-322b-459b-97b0-0c557f05d017-a3d1899c3344.small.png&w=48&q=75 1x, /_next/image?url=https%3A%2F%2Fprod-discovery.edx-cdn.org%2Fcdn-cgi%2Fimage%2Fwidth%3Dauto%2Cheight%3Dauto%2Cquality%3D75%2Cformat%3Dwebp%2Fmedia%2Fcourse%2Fimage%2Fda1b2400-322b-459b-97b0-0c557f05d017-a3d1899c3344.small.png&w=96&q=75 2x" src="/_next/image?url=https%3A%2F%2Fprod-discovery.edx-cdn.org%2Fcdn-cgi%2Fimage%2Fwidth%3Dauto%2Cheight%3Dauto%2Cquality%3D75%2Cformat%3Dwebp%2Fmedia%2Fcourse%2Fimage%2Fda1b2400-322b-459b-97b0-0c557f05d017-a3d1899c3344.small.png&w=96&q=75"/><div class="font-normal"><span class="text-sm lg:text-base block">CS50's Introduction to Computer Science</span><span class="text-xs lg:text-sm block">HarvardX | Course</span></div></a></li><li class="m-0 px-3 py-2 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src="/_next/image?url=https%3A%2F%2Fprod-discovery.edx-cdn.org%2Fcdn-cgi%2Fimage%2Fwidth%3Dauto%2Cheight%3Dauto%2Cquality%3D75%2Cformat%3Dwebp%2Fmedia%2Fcourse%2Fimage%2F32ab61e5-44b4-4316-ad59-9f04fc876e0a-aeb25306d62b.small.jpg&w=96&q=75"/><div class="font-normal"><span class="text-sm lg:text-base block">Artificial Intelligence: Implications for Business Strategy</span><span class="text-xs lg:text-sm block">MIT Sloan School of Management | Executive Education</span></div></a></li><li class="m-0 px-3 py-2 ProductSearch_searchListItem__5Bj11"><a href="/masters/micromasters/mitx-supply-chain-management?correlationId=44a397b0-4ed3-47f8-a7ba-617fd9636480" class="no-underline flex items-center"><img alt="Supply Chain Management" loading="lazy" width="36" height="36" decoding="async" data-nimg="1" class="object-cover overflow-clip my-0 mr-2 w-9 h-9" style="color:transparent" srcSet="/_next/image?url=https%3A%2F%2Fprod-discovery.edx-cdn.org%2Fcdn-cgi%2Fimage%2Fwidth%3Dauto%2Cheight%3Dauto%2Cquality%3D75%2Cformat%3Dwebp%2Fmedia%2Fprograms%2Fcard_images%2F2fc3236d-78a9-45a1-8c0c-fc290e74259e-f3b970b5cd3a.jpg&w=48&q=75 1x, /_next/image?url=https%3A%2F%2Fprod-discovery.edx-cdn.org%2Fcdn-cgi%2Fimage%2Fwidth%3Dauto%2Cheight%3Dauto%2Cquality%3D75%2Cformat%3Dwebp%2Fmedia%2Fprograms%2Fcard_images%2F2fc3236d-78a9-45a1-8c0c-fc290e74259e-f3b970b5cd3a.jpg&w=96&q=75 2x" src="/_next/image?url=https%3A%2F%2Fprod-discovery.edx-cdn.org%2Fcdn-cgi%2Fimage%2Fwidth%3Dauto%2Cheight%3Dauto%2Cquality%3D75%2Cformat%3Dwebp%2Fmedia%2Fprograms%2Fcard_images%2F2fc3236d-78a9-45a1-8c0c-fc290e74259e-f3b970b5cd3a.jpg&w=96&q=75"/><div class="font-normal"><span class="text-sm lg:text-base block">Supply Chain Management</span><span class="text-xs lg:text-sm block">MITx | MicroMasters</span></div></a></li><li class="m-0 px-3 py-2 ProductSearch_searchListItem__5Bj11"><a 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Advances in machine learning, artificial intelligence, and cybersecurity have led to growth in information technology. Computing technology plays a role in many fields of study and professions.<sup><a href="#5TaSekvLnGotXQAtdWOP4F">1</a></sup>Computer scientists create systems designed to understand big data structures, think like humans, and help predict the future. </p><p>Careers in computer science could be viable for learners whose strengths lie in mathematics and technology. As algorithms become more complex, computer science encompasses more fields and concentrations, and provides more diverse jobs. 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id="radix-:Rsjjttrkva:-content-Boot Camp" tabindex="0" class="mt-2 ring-offset-background focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring focus-visible:ring-offset-2"></div><div data-state="inactive" data-orientation="horizontal" role="tabpanel" aria-labelledby="radix-:Rsjjttrkva:-trigger-Masters" hidden="" id="radix-:Rsjjttrkva:-content-Masters" tabindex="0" class="mt-2 ring-offset-background focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring focus-visible:ring-offset-2"></div><div data-state="inactive" data-orientation="horizontal" role="tabpanel" aria-labelledby="radix-:Rsjjttrkva:-trigger-Bachelors" hidden="" id="radix-:Rsjjttrkva:-content-Bachelors" tabindex="0" class="mt-2 ring-offset-background focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring focus-visible:ring-offset-2"></div><div class="hidden lg:flex justify-center"><div role="tablist" aria-orientation="horizontal" class="inline-flex h-12 items-center 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transition-all focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring focus-visible:ring-offset-2 disabled:pointer-events-none disabled:opacity-50 data-[state=active]:bg-secondary data-[state=active]:text-primary-foreground data-[state=active]:shadow data-[state=active]:hover:bg-secondary no-underline font-normal text-[16px] text-primary hover:text-primary data-[state=active]:font-bold bg-white rounded-none first:rounded-tl-xl last:rounded-tr-xl" tabindex="-1" data-orientation="horizontal" data-radix-collection-item="">Bachelor's Programs (52)</button></div></div><div class="lg:hidden"><button type="button" role="combobox" aria-controls="radix-:Rssjjttrkva:" aria-expanded="false" aria-autocomplete="none" dir="ltr" data-state="closed" class="h-9 w-full justify-between whitespace-nowrap rounded bg-transparent px-3 py-2 text-sm ring-offset-background placeholder:text-putty-dark focus:outline-none focus:ring-1 focus:ring-ring disabled:cursor-not-allowed disabled:opacity-50 [&>span]:line-clamp-1 flex items-center border-solid border-[1px] border-primary shadow-none text-primary no-underline"><svg width="24" height="24" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg" role="img" focusable="false" aria-hidden="true"><path d="M3 17v2h6v-2H3ZM3 5v2h10V5H3Zm10 16v-2h8v-2h-8v-2h-2v6h2ZM7 9v2H3v2h4v2h2V9H7Zm14 4v-2H11v2h10Zm-6-4h2V7h4V5h-4V3h-2v6Z" fill="currentColor"></path></svg><span style="pointer-events:none"></span><svg width="15" height="15" viewBox="0 0 15 15" fill="none" xmlns="http://www.w3.org/2000/svg" class="h-4 w-4 opacity-50" aria-hidden="true"><path d="M4.93179 5.43179C4.75605 5.60753 4.75605 5.89245 4.93179 6.06819C5.10753 6.24392 5.39245 6.24392 5.56819 6.06819L7.49999 4.13638L9.43179 6.06819C9.60753 6.24392 9.89245 6.24392 10.0682 6.06819C10.2439 5.89245 10.2439 5.60753 10.0682 5.43179L7.81819 3.18179C7.73379 3.0974 7.61933 3.04999 7.49999 3.04999C7.38064 3.04999 7.26618 3.0974 7.18179 3.18179L4.93179 5.43179ZM10.0682 9.56819C10.2439 9.39245 10.2439 9.10753 10.0682 8.93179C9.89245 8.75606 9.60753 8.75606 9.43179 8.93179L7.49999 10.8636L5.56819 8.93179C5.39245 8.75606 5.10753 8.75606 4.93179 8.93179C4.75605 9.10753 4.75605 9.39245 4.93179 9.56819L7.18179 11.8182C7.35753 11.9939 7.64245 11.9939 7.81819 11.8182L10.0682 9.56819Z" fill="currentColor" fill-rule="evenodd" clip-rule="evenodd"></path></svg></button><select aria-hidden="true" tabindex="-1" style="position:absolute;border:0;width:1px;height:1px;padding:0;margin:-1px;overflow:hidden;clip:rect(0, 0, 0, 0);white-space:nowrap;word-wrap:normal"></select></div><div data-state="active" data-orientation="horizontal" role="tabpanel" aria-labelledby="radix-:Rsjjttrkva:-trigger-Course" id="radix-:Rsjjttrkva:-content-Course" tabindex="0" class="mt-2 ring-offset-background focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring focus-visible:ring-offset-2 flex flex-col max-w-[1128px] mx-auto" style="animation-duration:0s"><h3 class="mb-4">Courses</h3><div class="hidden lg:block"><div class="flex gap-4 py-4 flex-wrap undefined"></div></div><div class="lg:hidden"><div class="flex gap-4 py-4 overflow-x-scroll undefined"></div></div><div class="flex justify-center mx-auto mt-5"></div></div><div data-state="inactive" data-orientation="horizontal" role="tabpanel" aria-labelledby="radix-:Rsjjttrkva:-trigger-Executive Education" hidden="" id="radix-:Rsjjttrkva:-content-Executive Education" tabindex="0" class="mt-2 ring-offset-background focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring focus-visible:ring-offset-2 flex flex-col max-w-[1128px] mx-auto"></div><div data-state="inactive" data-orientation="horizontal" role="tabpanel" aria-labelledby="radix-:Rsjjttrkva:-trigger-Boot Camp" hidden="" id="radix-:Rsjjttrkva:-content-Boot Camp" tabindex="0" class="mt-2 ring-offset-background focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring focus-visible:ring-offset-2 flex flex-col max-w-[1128px] mx-auto"></div><div data-state="inactive" data-orientation="horizontal" role="tabpanel" aria-labelledby="radix-:Rsjjttrkva:-trigger-Masters" hidden="" id="radix-:Rsjjttrkva:-content-Masters" tabindex="0" class="mt-2 ring-offset-background focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring focus-visible:ring-offset-2 flex flex-col max-w-[1128px] mx-auto"></div><div data-state="inactive" data-orientation="horizontal" role="tabpanel" aria-labelledby="radix-:Rsjjttrkva:-trigger-Bachelors" hidden="" id="radix-:Rsjjttrkva:-content-Bachelors" tabindex="0" class="mt-2 ring-offset-background focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring focus-visible:ring-offset-2 flex flex-col max-w-[1128px] mx-auto"></div></div></div><div class="pt-0 pb-6 fullwidth bg-putty-100"><h3 class="mb-8 mt-0 text-2xl">Related Topics</h3><div class="flex gap-3 overflow-x-auto scroll-smooth not-prose"></div><div class="pt-4"></div></div><div class="flex flex-col gap-2 pb-10"><div class="Default_content__HO8we"><div id=""><h3>Why learn computer science?</h3><p>Understanding computer science can prepare learners to work in a broad range of computer science jobs. Computer science plays a role in data science, computer programming, engineering, business, education, government, and everyday life. A typical computer science jobmay require the ability to analyze problems and develop solutions related to computer hardware and software, as well as design computers and the software that run them.<sup><a href="#1VuNUcCM8Y9V0KcG61GECo">2</a></sup><sup><a href="#6C3e5Axew74AL2ViYWarW">3</a></sup>Certain roles may involve theoretical work in academics or practical work, such as software development. </p><p>Learners do not necessarily need to have a programming background in order to learn computer science, but taking a computer science course online or earning a computer science certificate can be a great path to enter the field. If an individual is interested in how to learn about computer science, they can also aim to earn an online computer science degree to strengthen their knowledge and put computing applications into practice. </p><h3>Computer science course curriculum </h3><p>Not all computer science courses look the same, but they are grounded in similar computer science principles. A sample curriculum of computer science courses may include topics in the following subjects: computer engineering, computer science, information systems, information technology, or software engineering. More advanced computer science classes may cover subjects such as designing and analyzing algorithms, human-computer interactions, or building applications for the internet of things (IoT).<sup><a href="#39l811Mfor93l3SVjCPwuZ">4</a></sup></p><p>Some computer science tutorialsare free to take for professional development, but learners can also opt for courses with credit, complete micro-degrees, earn <a class="text-link underline" href="https://edx.org/bachelors">bachelor's degrees</a> in computer science, or obtain a master's degree in a topic such as data science.</p><p>It’s important to have a basic understanding of mathematics, statistics, and some science knowledge to succeed in computer science jobs. And understanding some social sciences and humanities concepts can also help those pursuing data science jobs. </p></div></div><a class="subnav-item -mt-1" name="Computer science jobs" id="computer-science-jobs"></a><div class="Default_content__HO8we"><div id=""><h2>Computer science jobs</h2><p>There are many types of computer science jobs,<sup><a href="#VYOc1AM8nkeBqhGYWWclT">5</a></sup> including: </p><ul><li><p><b>Computer scientists</b>, who explore, construct, and implement complex computing systems, new computing languages, software systems, and other tools to improve user experience with computers.<sup><a href="#62jH52BNd3KyT6aWA4WaLC">6</a></sup></p></li><li><p><b>Network administrators</b>, who regulate the day-to-day operation of computer networks, including local area networks and other data communication.<sup><a href="#35HT1s1u9JXsIt92awZ7kX">7</a></sup></p></li><li><p><b>Software developers</b>, who design and develop software to allow users to conduct tasks and solve issues with the software.<sup><a href="#3a9cLD4grHUpSnxCoieHN4">8</a></sup></p></li></ul><p>Computer engineering, a closely related field, focuses on designing and developing systems such as cellular communications, medical devices, alarm systems, and military technologies. Individuals can learn computer science online to get a feel for which niche is right for them. </p><h3>How to become a computer scientist online</h3><p>When deciding how to learn about computer science, there are a few pathways a learner could take. One common path includes earning a <a class="text-link underline" href="https://www.edx.org/bachelors/computer-data-sciences">bachelor’s in data science or computer science</a>, followed by a <a class="text-link underline" href="https://www.edx.org/masters/online-masters-in-data-science">master’s degree in data science</a> or a related field, as the typical entry-level education required for computer scientist jobs is a master’s degree.<sup><a href="#Bn97f2yEYL8H8qz1v0tUE">9</a></sup></p><p>However, if a learner is looking for a second career or gaining additional knowledge and skills, taking computer science classes online via <a class="text-link underline" href="https://www.edx.org/boot-camps">boot camps</a> or short courses is another option to learn computer science for beginners, or Python online. Many computer science courses help learners understand the topics from a beginner’s level, so there are not always many prerequisites required beyond having an open mind for discovery. </p></div></div></div><div class="fullwidth max-w-none py-12 md:py-16 not-prose bg-primary-gradient"><div class="container"><h2 class="text-4xl md:text-6xl my-5 text-white italic"><span class="text-primary-foreground">More opportunities</span> for you to learn</h2><p class="text-lg leading-9 text-white">We've added 500+ learning opportunities to create one of the world's most comprehensive free-to-degree online learning platforms.</p><ul class="block md:grid md:grid-cols-2 md:gap-x-[100px] mx-auto lg:grid-cols-3"></ul></div></div><a class="subnav-item -mt-1" name="Computer science FAQ" id="computer-science-f-a-q"></a><a class="subnav-item" id="frequently-asked-questions"></a><div class="flex flex-col py-4 lg:py-16"><h2 class="mt-2 mb-4 text-3xl font-bold">Frequently Asked Questions</h2><div class="flex flex-col gap-3 [&_button]:no-underline [&_button]:text-gray-dark [&_button:hover]:text-gray-dark" data-orientation="vertical"><div data-state="closed" data-orientation="vertical" class="border-b AccordionTextItem_item__adF2E AccordionTextItem_item__adF2E"><h3 data-orientation="vertical" data-state="closed" class="flex"><button type="button" aria-controls="radix-:Rja4jjttrkva:" aria-expanded="false" data-state="closed" data-orientation="vertical" id="radix-:R3a4jjttrkva:" class="flex flex-1 text-left items-center justify-between py-4 text-sm font-medium transition-all hover:underline [&[data-state=open]>svg]:rotate-180 AccordionTextItem_trigger__CiZ_J AccordionTextItem_trigger__CiZ_J" data-radix-collection-item="">What does a computer scientist do?<svg width="15" height="15" viewBox="0 0 15 15" fill="none" xmlns="http://www.w3.org/2000/svg" class="h-4 w-4 shrink-0 text-putty-dark transition-transform duration-200"><path d="M3.13523 6.15803C3.3241 5.95657 3.64052 5.94637 3.84197 6.13523L7.5 9.56464L11.158 6.13523C11.3595 5.94637 11.6759 5.95657 11.8648 6.15803C12.0536 6.35949 12.0434 6.67591 11.842 6.86477L7.84197 10.6148C7.64964 10.7951 7.35036 10.7951 7.15803 10.6148L3.15803 6.86477C2.95657 6.67591 2.94637 6.35949 3.13523 6.15803Z" fill="currentColor" fill-rule="evenodd" clip-rule="evenodd"></path></svg></button></h3><div data-state="closed" id="radix-:Rja4jjttrkva:" hidden="" role="region" aria-labelledby="radix-:R3a4jjttrkva:" data-orientation="vertical" class="overflow-hidden text-sm data-[state=closed]:animate-accordion-up data-[state=open]:animate-accordion-down" style="--radix-accordion-content-height:var(--radix-collapsible-content-height);--radix-accordion-content-width:var(--radix-collapsible-content-width)"></div></div><div data-state="closed" data-orientation="vertical" class="border-b AccordionTextItem_item__adF2E AccordionTextItem_item__adF2E"><h3 data-orientation="vertical" data-state="closed" class="flex"><button type="button" aria-controls="radix-:Rla4jjttrkva:" aria-expanded="false" data-state="closed" data-orientation="vertical" id="radix-:R5a4jjttrkva:" class="flex flex-1 text-left items-center justify-between py-4 text-sm font-medium transition-all hover:underline [&[data-state=open]>svg]:rotate-180 AccordionTextItem_trigger__CiZ_J AccordionTextItem_trigger__CiZ_J" data-radix-collection-item="">Is computer science hard to learn?<svg width="15" height="15" viewBox="0 0 15 15" fill="none" xmlns="http://www.w3.org/2000/svg" class="h-4 w-4 shrink-0 text-putty-dark transition-transform duration-200"><path d="M3.13523 6.15803C3.3241 5.95657 3.64052 5.94637 3.84197 6.13523L7.5 9.56464L11.158 6.13523C11.3595 5.94637 11.6759 5.95657 11.8648 6.15803C12.0536 6.35949 12.0434 6.67591 11.842 6.86477L7.84197 10.6148C7.64964 10.7951 7.35036 10.7951 7.15803 10.6148L3.15803 6.86477C2.95657 6.67591 2.94637 6.35949 3.13523 6.15803Z" fill="currentColor" fill-rule="evenodd" clip-rule="evenodd"></path></svg></button></h3><div data-state="closed" id="radix-:Rla4jjttrkva:" hidden="" role="region" aria-labelledby="radix-:R5a4jjttrkva:" data-orientation="vertical" class="overflow-hidden text-sm data-[state=closed]:animate-accordion-up data-[state=open]:animate-accordion-down" style="--radix-accordion-content-height:var(--radix-collapsible-content-height);--radix-accordion-content-width:var(--radix-collapsible-content-width)"></div></div><div data-state="closed" data-orientation="vertical" class="border-b AccordionTextItem_item__adF2E AccordionTextItem_item__adF2E"><h3 data-orientation="vertical" data-state="closed" class="flex"><button type="button" aria-controls="radix-:Rna4jjttrkva:" aria-expanded="false" data-state="closed" data-orientation="vertical" id="radix-:R7a4jjttrkva:" class="flex flex-1 text-left items-center justify-between py-4 text-sm font-medium transition-all hover:underline [&[data-state=open]>svg]:rotate-180 AccordionTextItem_trigger__CiZ_J AccordionTextItem_trigger__CiZ_J" data-radix-collection-item="">What skills do I need before learning computer science?<svg width="15" height="15" viewBox="0 0 15 15" fill="none" xmlns="http://www.w3.org/2000/svg" class="h-4 w-4 shrink-0 text-putty-dark transition-transform duration-200"><path d="M3.13523 6.15803C3.3241 5.95657 3.64052 5.94637 3.84197 6.13523L7.5 9.56464L11.158 6.13523C11.3595 5.94637 11.6759 5.95657 11.8648 6.15803C12.0536 6.35949 12.0434 6.67591 11.842 6.86477L7.84197 10.6148C7.64964 10.7951 7.35036 10.7951 7.15803 10.6148L3.15803 6.86477C2.95657 6.67591 2.94637 6.35949 3.13523 6.15803Z" fill="currentColor" fill-rule="evenodd" clip-rule="evenodd"></path></svg></button></h3><div data-state="closed" id="radix-:Rna4jjttrkva:" hidden="" role="region" aria-labelledby="radix-:R7a4jjttrkva:" data-orientation="vertical" class="overflow-hidden text-sm data-[state=closed]:animate-accordion-up data-[state=open]:animate-accordion-down" style="--radix-accordion-content-height:var(--radix-collapsible-content-height);--radix-accordion-content-width:var(--radix-collapsible-content-width)"></div></div><div data-state="closed" data-orientation="vertical" class="border-b AccordionTextItem_item__adF2E AccordionTextItem_item__adF2E"><h3 data-orientation="vertical" data-state="closed" class="flex"><button type="button" aria-controls="radix-:Rpa4jjttrkva:" aria-expanded="false" data-state="closed" data-orientation="vertical" id="radix-:R9a4jjttrkva:" class="flex flex-1 text-left items-center justify-between py-4 text-sm font-medium transition-all hover:underline [&[data-state=open]>svg]:rotate-180 AccordionTextItem_trigger__CiZ_J AccordionTextItem_trigger__CiZ_J" data-radix-collection-item="">How long does it take to learn computer science?<svg width="15" height="15" viewBox="0 0 15 15" fill="none" xmlns="http://www.w3.org/2000/svg" class="h-4 w-4 shrink-0 text-putty-dark transition-transform duration-200"><path d="M3.13523 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AccordionTextItem_trigger__CiZ_J" data-radix-collection-item="">What is the difference between computer science and computer engineering?<svg width="15" height="15" viewBox="0 0 15 15" fill="none" xmlns="http://www.w3.org/2000/svg" class="h-4 w-4 shrink-0 text-putty-dark transition-transform duration-200"><path d="M3.13523 6.15803C3.3241 5.95657 3.64052 5.94637 3.84197 6.13523L7.5 9.56464L11.158 6.13523C11.3595 5.94637 11.6759 5.95657 11.8648 6.15803C12.0536 6.35949 12.0434 6.67591 11.842 6.86477L7.84197 10.6148C7.64964 10.7951 7.35036 10.7951 7.15803 10.6148L3.15803 6.86477C2.95657 6.67591 2.94637 6.35949 3.13523 6.15803Z" fill="currentColor" fill-rule="evenodd" clip-rule="evenodd"></path></svg></button></h3><div data-state="closed" id="radix-:Rta4jjttrkva:" hidden="" role="region" aria-labelledby="radix-:Rda4jjttrkva:" data-orientation="vertical" class="overflow-hidden text-sm data-[state=closed]:animate-accordion-up data-[state=open]:animate-accordion-down" style="--radix-accordion-content-height:var(--radix-collapsible-content-height);--radix-accordion-content-width:var(--radix-collapsible-content-width)"></div></div></div></div><ol><li id="5TaSekvLnGotXQAtdWOP4F"><p><a class="text-link underline" href="https://ccecc.acm.org/guidance">Curricular Guidance: The Sub-Disciplines of Computing</a>. <i>Association for Computing Machinery Committee for Computing Education in Community Colleges</i>. Retrieved August 22, 2022. </p></li><li id="1VuNUcCM8Y9V0KcG61GECo"><p><a class="text-link underline" href="https://www.acm.org/binaries/content/assets/education/curricula-recommendations/cc2020.pdf">Computing Curricula</a>. 2020. <i>Association for Computing Machinery</i>. (2021). Retrieved August 22, 2022. </p></li><li id="6C3e5Axew74AL2ViYWarW"><p><a class="text-link underline" href="https://www.onetonline.org/link/summary/15-1221.00">Computer and Information Research Scientists</a>. O-Net Online. Retrieved August 22, 2022.</p></li><li id="39l811Mfor93l3SVjCPwuZ"><p><a class="text-link underline" href="https://www.acm.org/education/curricula-recommendations">Curricula Recommendations</a>. <i>Association for Computing Machinery</i>. Retrieved August 22, 2022. </p></li><li id="VYOc1AM8nkeBqhGYWWclT"><p><a class="text-link underline" href="https://www.bls.gov/ooh/computer-and-information-technology/home.htm">Computer and Information Technology Occupations</a>. (2022).<i> U.S. Bureau of Labor Statistics</i>. Retrieved August 22, 2022. </p></li><li id="62jH52BNd3KyT6aWA4WaLC"><p><a class="text-link underline" href="https://www.bls.gov/ooh/computer-and-information-technology/computer-and-information-research-scientists.htm#tab-2">Computer and Information Research Scientists: What Computer and Information Research Scientists Do</a>. (2022).<i> U.S. Bureau of Labor Statistics</i>. Retrieved August 22, 2022. </p></li><li id="35HT1s1u9JXsIt92awZ7kX"><p><a class="text-link underline" href="https://www.bls.gov/ooh/computer-and-information-technology/network-and-computer-systems-administrators.htm#tab-2">Network and Computer Systems Administrators: What Network and Computer Systems Administrators Do</a>. (2022). <i>U.S. Bureau of Labor Statistics</i>. Retrieved August 22, 2022.</p></li><li id="3a9cLD4grHUpSnxCoieHN4"><p><a class="text-link underline" href="https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm#tab-2">Software Developers, Quality Assurance Analysts, and Testers: What Software Developers, Quality Assurance Analysts, and Testers Do</a>. (2021). <i>U.S. Bureau of Labor Statistics</i>. Retrieved August 22, 2022. </p></li><li id="Bn97f2yEYL8H8qz1v0tUE"><p><a class="text-link underline" href="http://bls.gov/ooh/computer-and-information-technology/computer-and-information-research-scientists.htm">Computer and Information Research Scientists: Summary</a>. (2022). <i>U.S. Bureau of Labor Statistics</i>. 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hover:bg-primary\",\"name\":\"engineering\",\"position\":\"10\"}]]}]}],[\"$\",\"div\",null,{\"className\":\"pt-4\",\"children\":[\"$\",\"$L16\",null,{\"children\":[\"$\",\"$L2c8\",null,{\"href\":\"/learn\",\"text\":\"View all topics\",\"html_id\":\"view-all-topics-link\",\"location\":\"related-topics\",\"element_type\":\"LINK\",\"class_name\":\"text-gray-dark text-sm underline hover:text-[1f1f1f]\"}]}]}]]}],[\"$\",\"div\",\"4\",{\"className\":\"flex flex-col gap-2 pb-10\",\"children\":[[\"$\",\"div\",null,{\"className\":\"Default_content__HO8we\",\"children\":[\"$\",\"div\",null,{\"id\":\"\",\"children\":[[\"$\",\"h3\",\"0\",{\"children\":\"Why learn computer science?\"}],[\"$\",\"p\",\"1\",{\"children\":[\"Understanding computer science can prepare learners to work in a broad range of computer science jobs. Computer science plays a role in data science, computer programming, engineering, business, education, government, and everyday life. A typical computer science jobmay require the ability to analyze problems and develop solutions related to computer hardware and software, as well as design computers and the software that run them.\",[\"$\",\"sup\",\"1\",{\"children\":[\"$\",\"a\",null,{\"href\":\"#1VuNUcCM8Y9V0KcG61GECo\",\"children\":\"2\"}]}],[\"$\",\"sup\",\"2\",{\"children\":[\"$\",\"a\",null,{\"href\":\"#6C3e5Axew74AL2ViYWarW\",\"children\":\"3\"}]}],\"Certain roles may involve theoretical work in academics or practical work, such as software development. \"]}],[\"$\",\"p\",\"2\",{\"children\":\"Learners do not necessarily need to have a programming background in order to learn computer science, but taking a computer science course online or earning a computer science certificate can be a great path to enter the field. If an individual is interested in how to learn about computer science, they can also aim to earn an online computer science degree to strengthen their knowledge and put computing applications into practice. \"}],[\"$\",\"h3\",\"3\",{\"children\":\"Computer science course curriculum \"}],[\"$\",\"p\",\"4\",{\"children\":[\"Not all computer science courses look the same, but they are grounded in similar computer science principles. A sample curriculum of computer science courses may include topics in the following subjects: computer engineering, computer science, information systems, information technology, or software engineering. More advanced computer science classes may cover subjects such as designing and analyzing algorithms, human-computer interactions, or building applications for the internet of things (IoT).\",[\"$\",\"sup\",\"1\",{\"children\":[\"$\",\"a\",null,{\"href\":\"#39l811Mfor93l3SVjCPwuZ\",\"children\":\"4\"}]}]]}],[\"$\",\"p\",\"5\",{\"children\":[\"Some computer science tutorialsare free to take for professional development, but learners can also opt for courses with credit, complete micro-degrees, earn \",[\"$\",\"a\",\"1\",{\"className\":\"text-link underline\",\"href\":\"https://edx.org/bachelors\",\"children\":\"bachelor's degrees\"}],\" in computer science, or obtain a master's degree in a topic such as data science.\"]}],[\"$\",\"p\",\"6\",{\"children\":\"It’s important to have a basic understanding of mathematics, statistics, and some science knowledge to succeed in computer science jobs. And understanding some social sciences and humanities concepts can also help those pursuing data science jobs. \"}]]}]}],[\"$\",\"a\",\"1\",{\"className\":\"subnav-item -mt-1\",\"name\":\"Computer science jobs\",\"id\":\"computer-science-jobs\",\"children\":\"$undefined\"}],[\"$\",\"div\",null,{\"className\":\"Default_content__HO8we\",\"children\":[\"$\",\"div\",null,{\"id\":\"\",\"children\":[[\"$\",\"h2\",\"0\",{\"children\":\"Computer science jobs\"}],[\"$\",\"p\",\"1\",{\"children\":[\"There are many types of computer science jobs,\",[\"$\",\"sup\",\"1\",{\"children\":[\"$\",\"a\",null,{\"href\":\"#VYOc1AM8nkeBqhGYWWclT\",\"children\":\"5\"}]}],\" including: \"]}],[\"$\",\"ul\",\"2\",{\"children\":[[\"$\",\"li\",\"0\",{\"children\":[\"$\",\"p\",null,{\"children\":[[\"$\",\"b\",\"0\",{\"children\":\"Computer scientists\"}],\", who explore, construct, and implement complex computing systems, new computing languages, software systems, and other tools to improve user experience with computers.\",[\"$\",\"sup\",\"2\",{\"children\":[\"$\",\"a\",null,{\"href\":\"#62jH52BNd3KyT6aWA4WaLC\",\"children\":\"6\"}]}]]}]}],[\"$\",\"li\",\"1\",{\"children\":[\"$\",\"p\",null,{\"children\":[[\"$\",\"b\",\"0\",{\"children\":\"Network administrators\"}],\", who regulate the day-to-day operation of computer networks, including local area networks and other data communication.\",[\"$\",\"sup\",\"2\",{\"children\":[\"$\",\"a\",null,{\"href\":\"#35HT1s1u9JXsIt92awZ7kX\",\"children\":\"7\"}]}]]}]}],[\"$\",\"li\",\"2\",{\"children\":[\"$\",\"p\",null,{\"children\":[[\"$\",\"b\",\"0\",{\"children\":\"Software developers\"}],\", who design and develop software to allow users to conduct tasks and solve issues with the software.\",[\"$\",\"sup\",\"2\",{\"children\":[\"$\",\"a\",null,{\"href\":\"#3a9cLD4grHUpSnxCoieHN4\",\"children\":\"8\"}]}]]}]}]]}],[\"$\",\"p\",\"3\",{\"children\":\"Computer engineering, a closely related field, focuses on designing and developing systems such as cellular communications, medical devices, alarm systems, and military technologies. Individuals can learn computer science online to get a feel for which niche is right for them. \"}],[\"$\",\"h3\",\"4\",{\"children\":\"How to become a computer scientist online\"}],[\"$\",\"p\",\"5\",{\"children\":[\"When deciding how to learn about computer science, there are a few pathways a learner could take. One common path includes earning a \",[\"$\",\"a\",\"1\",{\"className\":\"text-link underline\",\"href\":\"https://www.edx.org/bachelors/computer-data-sciences\",\"children\":\"bachelor’s in data science or computer science\"}],\", followed by a \",[\"$\",\"a\",\"3\",{\"className\":\"text-link underline\",\"href\":\"https://www.edx.org/masters/online-masters-in-data-science\",\"children\":\"master’s degree in data science\"}],\" or a related field, as the typical entry-level education required for computer scientist jobs is a master’s degree.\",[\"$\",\"sup\",\"5\",{\"children\":[\"$\",\"a\",null,{\"href\":\"#Bn97f2yEYL8H8qz1v0tUE\",\"children\":\"9\"}]}]]}],[\"$\",\"p\",\"6\",{\"children\":[\"However, if a learner is looking for a second career or gaining additional knowledge and skills, taking computer science classes online via \",[\"$\",\"a\",\"1\",{\"className\":\"text-link underline\",\"href\":\"https://www.edx.org/boot-camps\",\"children\":\"boot camps\"}],\" or short courses is another option to learn computer science for beginners, or Python online. Many computer science courses help learners understand the topics from a beginner’s level, so there are not always many prerequisites required beyond having an open mind for discovery. \"]}]]}]}]]}],[\"$\",\"$L2c9\",null,{\"theme\":\"gradient\",\"children\":[]}],[\"$\",\"a\",\"6\",{\"className\":\"subnav-item -mt-1\",\"name\":\"Computer science FAQ\",\"id\":\"computer-science-f-a-q\",\"children\":\"$undefined\"}],[[\"$\",\"a\",null,{\"className\":\"subnav-item\",\"id\":\"frequently-asked-questions\"}],[\"$\",\"div\",null,{\"className\":\"flex flex-col py-4 lg:py-16\",\"children\":[[\"$\",\"h2\",null,{\"className\":\"mt-2 mb-4 text-3xl font-bold\",\"children\":\"Frequently Asked Questions\"}],[\"$\",\"$L2ca\",null,{\"type\":\"single\",\"collapsible\":true,\"className\":\"flex flex-col gap-3 [\u0026_button]:no-underline [\u0026_button]:text-gray-dark [\u0026_button:hover]:text-gray-dark\",\"children\":[[\"$\",\"$L2cb\",null,{\"value\":\"What does a computer scientist do?\",\"className\":\"AccordionTextItem_item__adF2E AccordionTextItem_item__adF2E\",\"children\":[[\"$\",\"$L2cc\",null,{\"className\":\"AccordionTextItem_trigger__CiZ_J AccordionTextItem_trigger__CiZ_J\",\"children\":\"What does a computer scientist do?\"}],[\"$\",\"$L2cd\",null,{\"className\":\"AccordionTextItem_content__G0vl3 AccordionTextItem_content__G0vl3\",\"children\":[\"$\",\"p\",null,{\"children\":\"Computer scientists design and develop innovative uses for new and existing computer technology. Their jobs may involve developing new computing languages and conducting experiments to test how systems work. Computer science borrows techniques from data science and machine learning.\"}]}]]}],[\"$\",\"$L2cb\",null,{\"value\":\"Is computer science hard to learn?\",\"className\":\"AccordionTextItem_item__adF2E AccordionTextItem_item__adF2E\",\"children\":[[\"$\",\"$L2cc\",null,{\"className\":\"AccordionTextItem_trigger__CiZ_J AccordionTextItem_trigger__CiZ_J\",\"children\":\"Is computer science hard to learn?\"}],[\"$\",\"$L2cd\",null,{\"className\":\"AccordionTextItem_content__G0vl3 AccordionTextItem_content__G0vl3\",\"children\":[\"$\",\"p\",null,{\"children\":\"Computer science may not be hard to learn for those whose strengths lie in mathematics, statistics, technology, and computing. A learner’s aptitude for computer science depends on their prior knowledge, experience, and dedication to study, among other factors.\"}]}]]}],[\"$\",\"$L2cb\",null,{\"value\":\"What skills do I need before learning computer science?\",\"className\":\"AccordionTextItem_item__adF2E AccordionTextItem_item__adF2E\",\"children\":[[\"$\",\"$L2cc\",null,{\"className\":\"AccordionTextItem_trigger__CiZ_J AccordionTextItem_trigger__CiZ_J\",\"children\":\"What skills do I need before learning computer science?\"}],[\"$\",\"$L2cd\",null,{\"className\":\"AccordionTextItem_content__G0vl3 AccordionTextItem_content__G0vl3\",\"children\":[\"$\",\"p\",null,{\"children\":\"When learning computer science, it’s important to build analytical skills, critical reasoning, and creativity. Computer scientists need to know how to problem-solve complex computing issues that can be found in software development or computer engineering. A basic understanding of mathematics, statistics, and some science can help, too.\"}]}]]}],[\"$\",\"$L2cb\",null,{\"value\":\"How long does it take to learn computer science?\",\"className\":\"AccordionTextItem_item__adF2E AccordionTextItem_item__adF2E\",\"children\":[[\"$\",\"$L2cc\",null,{\"className\":\"AccordionTextItem_trigger__CiZ_J AccordionTextItem_trigger__CiZ_J\",\"children\":\"How long does it take to learn computer science?\"}],[\"$\",\"$L2cd\",null,{\"className\":\"AccordionTextItem_content__G0vl3 AccordionTextItem_content__G0vl3\",\"children\":[\"$\",\"p\",null,{\"children\":\"It can take anywhere from several months to several years to learn computer science, depending on a learner’s educational and professional background. To learn computer science online, a program can be entirely self-paced. Degree programs can take several years to complete, depending on a learner’s schedule preferences. For boot camps and short courses, it can take several months or several years to build the skills required for becoming a web developer or proficiency for other careers in computer science. \"}]}]]}],[\"$\",\"$L2cb\",null,{\"value\":\"What are the key principles of computer science?\",\"className\":\"AccordionTextItem_item__adF2E AccordionTextItem_item__adF2E\",\"children\":[[\"$\",\"$L2cc\",null,{\"className\":\"AccordionTextItem_trigger__CiZ_J AccordionTextItem_trigger__CiZ_J\",\"children\":\"What are the key principles of computer science?\"}],[\"$\",\"$L2cd\",null,{\"className\":\"AccordionTextItem_content__G0vl3 AccordionTextItem_content__G0vl3\",\"children\":[\"$\",\"p\",null,{\"children\":\"Key computer science principles include computation, automation, evaluation, communication, coordination, recollection, and design.\"}]}]]}],[\"$\",\"$L2cb\",null,{\"value\":\"What is the difference between computer science and computer engineering?\",\"className\":\"AccordionTextItem_item__adF2E AccordionTextItem_item__adF2E\",\"children\":[[\"$\",\"$L2cc\",null,{\"className\":\"AccordionTextItem_trigger__CiZ_J AccordionTextItem_trigger__CiZ_J\",\"children\":\"What is the difference between computer science and computer engineering?\"}],[\"$\",\"$L2cd\",null,{\"className\":\"AccordionTextItem_content__G0vl3 AccordionTextItem_content__G0vl3\",\"children\":[\"$\",\"p\",null,{\"children\":\"Computer science focuses on building innovative computing technology. On the other hand, computer engineering — traditionally considered a combination of computer science and electrical engineering — focuses on designing, implementing, and maintaining software and hardware of computer systems.\"}]}]]}]]}]]}]],[\"$\",\"ol\",\"8\",{\"children\":[[\"$\",\"li\",\"0\",{\"id\":\"5TaSekvLnGotXQAtdWOP4F\",\"children\":[\"$\",\"p\",null,{\"children\":[[\"$\",\"a\",\"0\",{\"className\":\"text-link underline\",\"href\":\"https://ccecc.acm.org/guidance\",\"children\":\"Curricular Guidance: The Sub-Disciplines of Computing\"}],\". \",[\"$\",\"i\",\"2\",{\"children\":\"Association for Computing Machinery Committee for Computing Education in Community Colleges\"}],\". Retrieved August 22, 2022. \"]}]}],[\"$\",\"li\",\"1\",{\"id\":\"1VuNUcCM8Y9V0KcG61GECo\",\"children\":[\"$\",\"p\",null,{\"children\":[[\"$\",\"a\",\"0\",{\"className\":\"text-link underline\",\"href\":\"https://www.acm.org/binaries/content/assets/education/curricula-recommendations/cc2020.pdf\",\"children\":\"Computing Curricula\"}],\". 2020. \",[\"$\",\"i\",\"2\",{\"children\":\"Association for Computing Machinery\"}],\". (2021). Retrieved August 22, 2022. \"]}]}],[\"$\",\"li\",\"2\",{\"id\":\"6C3e5Axew74AL2ViYWarW\",\"children\":[\"$\",\"p\",null,{\"children\":[[\"$\",\"a\",\"0\",{\"className\":\"text-link underline\",\"href\":\"https://www.onetonline.org/link/summary/15-1221.00\",\"children\":\"Computer and Information Research Scientists\"}],\". O-Net Online. Retrieved August 22, 2022.\"]}]}],[\"$\",\"li\",\"3\",{\"id\":\"39l811Mfor93l3SVjCPwuZ\",\"children\":[\"$\",\"p\",null,{\"children\":[[\"$\",\"a\",\"0\",{\"className\":\"text-link underline\",\"href\":\"https://www.acm.org/education/curricula-recommendations\",\"children\":\"Curricula Recommendations\"}],\". \",[\"$\",\"i\",\"2\",{\"children\":\"Association for Computing Machinery\"}],\". Retrieved August 22, 2022. \"]}]}],[\"$\",\"li\",\"4\",{\"id\":\"VYOc1AM8nkeBqhGYWWclT\",\"children\":[\"$\",\"p\",null,{\"children\":[[\"$\",\"a\",\"0\",{\"className\":\"text-link underline\",\"href\":\"https://www.bls.gov/ooh/computer-and-information-technology/home.htm\",\"children\":\"Computer and Information Technology Occupations\"}],\". (2022).\",[\"$\",\"i\",\"2\",{\"children\":\" U.S. Bureau of Labor Statistics\"}],\". Retrieved August 22, 2022. \"]}]}],[\"$\",\"li\",\"5\",{\"id\":\"62jH52BNd3KyT6aWA4WaLC\",\"children\":[\"$\",\"p\",null,{\"children\":[[\"$\",\"a\",\"0\",{\"className\":\"text-link underline\",\"href\":\"https://www.bls.gov/ooh/computer-and-information-technology/computer-and-information-research-scientists.htm#tab-2\",\"children\":\"Computer and Information Research Scientists: What Computer and Information Research Scientists Do\"}],\". (2022).\",[\"$\",\"i\",\"2\",{\"children\":\" U.S. Bureau of Labor Statistics\"}],\". Retrieved August 22, 2022. \"]}]}],[\"$\",\"li\",\"6\",{\"id\":\"35HT1s1u9JXsIt92awZ7kX\",\"children\":[\"$\",\"p\",null,{\"children\":[[\"$\",\"a\",\"0\",{\"className\":\"text-link underline\",\"href\":\"https://www.bls.gov/ooh/computer-and-information-technology/network-and-computer-systems-administrators.htm#tab-2\",\"children\":\"Network and Computer Systems Administrators: What Network and Computer Systems Administrators Do\"}],\". (2022). \",[\"$\",\"i\",\"2\",{\"children\":\"U.S. Bureau of Labor Statistics\"}],\". Retrieved August 22, 2022.\"]}]}],[\"$\",\"li\",\"7\",{\"id\":\"3a9cLD4grHUpSnxCoieHN4\",\"children\":[\"$\",\"p\",null,{\"children\":[[\"$\",\"a\",\"0\",{\"className\":\"text-link underline\",\"href\":\"https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm#tab-2\",\"children\":\"Software Developers, Quality Assurance Analysts, and Testers: What Software Developers, Quality Assurance Analysts, and Testers Do\"}],\". (2021). \",[\"$\",\"i\",\"2\",{\"children\":\"U.S. Bureau of Labor Statistics\"}],\". Retrieved August 22, 2022. \"]}]}],[\"$\",\"li\",\"8\",{\"id\":\"Bn97f2yEYL8H8qz1v0tUE\",\"children\":[\"$\",\"p\",null,{\"children\":[[\"$\",\"a\",\"0\",{\"className\":\"text-link underline\",\"href\":\"http://bls.gov/ooh/computer-and-information-technology/computer-and-information-research-scientists.htm\",\"children\":\"Computer and Information Research Scientists: Summary\"}],\". (2022). \",[\"$\",\"i\",\"2\",{\"children\":\"U.S. Bureau of Labor Statistics\"}],\". Retrieved August 22, 2022. \"]}]}]]}]]}]]}]}]]}],[\"$\",\"div\",null,{\"className\":\"bg-primary text-primary-foreground pt-16\",\"children\":[\"$\",\"footer\",null,{\"className\":\"flex justify-between max-w-screen-xl mx-auto px-4 pb-4 \",\"children\":[\"$\",\"div\",null,{\"className\":\"flex flex-col w-full\",\"children\":[[\"$\",\"div\",null,{\"className\":\"flex flex-wrap justify-between mb-6 w-full\",\"children\":[[\"$\",\"a\",null,{\"href\":\"/\",\"className\":\"mb-6\",\"children\":[\"$\",\"$L21\",null,{\"src\":\"/trademark-logos/edx-by-2u-white.svg\",\"alt\":\"edX homepage\",\"width\":127,\"height\":67,\"className\":\"optanon-category-C0001\",\"data-ot-ignore\":true}]}],[\"$\",\"div\",null,{\"children\":[\"$\",\"div\",null,{\"className\":\"flex gap-6 mb-4 items-center justify-center align-middle\",\"children\":[[\"$\",\"a\",null,{\"className\":\"text-white\",\"href\":\"https://www.facebook.com/EdxOnline\",\"target\":\"_blank\",\"role\":\"button\",\"aria-label\":\"Visit our 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Efficient data structures are key for designing efficient algorithms and obtaining maintainable software design.\u003c/p\u003e\n\u003cp\u003eIn this Computer Science course, you will start by learning basic data types, such as numbers, and gradually build a conceptual framework for organizing and managing efficient structures.\u003c/p\u003e\n\u003cp\u003eTopics covered:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eBasic Data Types, Notion of an Abstract Data Type\u003c/li\u003e\n\u003cli\u003eMathematical Properties of Sequences\u003c/li\u003e\n\u003cli\u003eSpecial Types of Sequences: Stacks, Queues, Strings\u003c/li\u003e\n\u003cli\u003eImplementation of Sequence Type: Arrays and Linked Lists\u003c/li\u003e\n\u003cli\u003eTrees\u003c/li\u003e\n\u003cli\u003eSets and Maps\u003c/li\u003e\n\u003cli\u003eGraphs\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003ePreliminary understanding of implementing sequence structures such as stacks, queues, and linked lists, will also be covered.\u003c/p\u003e\n\u003cp\u003eThis course is part of the \u003ca href=\"https://www.edx.org/xseries/fundamentals-computer-science\"\u003eFundamentals of Computer Science XSeries Program\u003c/a\u003e:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/programming-basics-iitbombayx-cs101-1x\"\u003eProgramming Basics\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/object-orie"])</script><script>self.__next_f.push([1,"nted-programming-iitbombayx-cs101-2x\"\u003eObject-Oriented Programming\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/implementation-data-structures-iitbombayx-cs213-2x\"\u003eImplementation of Data Structures\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/algorithms-2\"\u003eAlgorithms\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e2f6:T58b,\u003cp\u003eThis is Harvard’s famous CS50 course bundled together with CS50’s Introduction to Python as one program: Computer Science for Python Programming. Get an introduction to the intellectual enterprises of computer science and the art of programming using a language called Python.\u003c/p\u003e\r\n \r\n\u003cp\u003eIn this two-course Professional Certificate program you can kick off your programming journey with an Introduction to Computer Science (CS50x), which focuses on computer science more generally as well as an entry into programming with Python along with C, SQL, and JavaScript, plus HTML and CSS.\u003c/p\u003e\r\n\r\n\u003cp\u003eTo further your skills for programming with Python, you can then turn to course 2, CS50’s Introduction to Programming with Python (CS50P). In this course, you will learn how to read and write code as well as how to test and \"debug\" it. This course recaps lessons learned in CS50x and then dives all the more deeply into Python itself.\u003c/p\u003e\r\n \r\n\u003cp\u003eThe program features hands-on opportunities for exercises inspired by real-world programming problems. No software required except for a web browser, or you can write code on your own PC or Mac.\r\nBoth courses in this program are entry-level courses for students with no programming experience or prior background, taught by \u003ca href=\"edx.org/bio/david-j-malan\"\u003eDavid J. Malan\u003c/a\u003e who teaches CS50 on the Harvard campus - one of Harvard University’s largest courses!\u003c/p\u003e2f7:T5dd,\u003cp\u003eThe demand for expertise in AI and machine learning is growing rapidly. By enabling new technologies like self-driving cars and recommendation systems or improving old ones like medical diagnostics and search engines, AI is transforming how we live, work, and play. This series will enable you to take the first steps t"])</script><script>self.__next_f.push([1,"oward understanding programming fundamentals so you can solve important real-world problems and future-proof your career.\u003c/p\u003e\r\n\r\n\u003cp\u003eThis professional certificate series combines CS50’s legendary Introduction to Computer Science course with a new program that takes a deep dive into the concepts and algorithms at the foundation of modern artificial intelligence. This series will lead you through the most popular undergraduate course at Harvard, where you’ll learn the common programming languages, then carries that foundation through CS50’s Introduction to Artificial Intelligence with Python. Through hands-on projects, you’ll gain exposure to the theory behind graph search algorithms, classification, optimization, reinforcement learning, and other topics in artificial intelligence.\u003c/p\u003e\r\n\r\n\u003cp\u003eBy course’s end, students emerge with experience in libraries for machine learning as well as knowledge of artificial intelligence principles that enable them to design intelligent systems of their own. Enroll now to gain expertise in one of the fastest-growing domains of computer science from the creators of one of the most popular computer science courses ever.\u003c/p\u003e2f8:T8c9,"])</script><script>self.__next_f.push([1,"\u003cp\u003e\u003cspan lang=\"EN-US\"\u003eDo you want to learn more about data and gain programming experience? If yes, this is the right course for you to start!\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e“Big data”, “data science”, “data-mining” and “artificial intelligence” are all popular terms that are often encountered nowadays in the academic and in business worlds.\u003c/p\u003e\n\u003cp\u003eComputer Science is a field where the usage of computers and “computations” have continuously evolved. As computational power increases, computation becomes an indispensable tool for solving complex problems and making predictions. We are now able to “compute” various things from DNA sequencing to aerodynamics simulations and weather forecasting.\u003c/p\u003e\n\u003cp\u003eIn this course, you will learn the essence of computer science. You will obtain an overview of cutting-edge computer science as well as learn the basics and introductory level knowledge of computer science, while experiencing, designing and writing your own simple programs. This revised course consists of 5 weekly units. A separate course covering the same content is also offered where the lectures are given in Japanese. \u003c/p\u003e\n\u003cp\u003eThe course begins by introducing the notion of computation and data and how things work inside a computer. Before jumping into advanced topics like encryption and cryptanalysis, we will discover important notions like \"arrays\", \"characters\" and \"strings\" and we will know more about functions and subroutines throughout the lectures. Along the way we will practice with exercises to have a hands-on experience and deeper understanding of the explained notions. All exercises have files that can be downloaded and used. A detailed explanation about setting up the environment to run the programs using the language Ruby is provided at the beginning of the course.\u003c/p\u003e\n\u003cp\u003eBy the end of this course you will be able to write your own programs for encryption and decryption of English texts. The course concludes with a general overview of the recent progress and research trends in the computer science field. This last part covers topics discussing the nature of computation as well as applications of computation in our modern society such as simulations, data mining and artificial intelligence AI.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"2f9:T482,\u003cp\u003ePerhaps the most popular data science methodologies come from machine learning. What distinguishes machine learning from other computer guided decision processes is that it builds prediction algorithms using data. Some of the most popular products that use machine learning include the handwriting readers implemented by the postal service, speech recognition, movie recommendation systems, and spam detectors. \u003c/p\u003e\n\u003cp\u003eIn this course,part ofour\u003ca href=\"https://www.edx.org/professional-certificate/harvardx-data-science\"\u003eProfessional Certificate Program in Data Science\u003c/a\u003e, you will learn popular machine learning algorithms, principal component analysis, and regularization by building a movie recommendation system. \u003c/p\u003e\n\u003cp\u003eYou will learn about training data, and how to use a set of data to discover potentially predictive relationships. As you build the movie recommendation system, you will learn how to train algorithms using training data so you can predict the outcome for future datasets. You will also learn about overtraining and techniques to avoid it such as cross-validation. All of these skills are fundamental to machine learning.\u003c/p\u003e2fa:T629,\u003cp\u003eWelcome to the self paced course, \u003cem\u003eAlgorithms: Design and Analysis\u003c/em\u003e! Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth.\u003c/p\u003e\n\u003cp\u003eThis specialization is an introduction to algorithms for learners with at least a little programming experience. The specialization is rigorous but emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details. After completing this specialization, you will be well-positioned to ace your technical interviews and speak fluently about algorithms with other programmers and computer scientists.\u003c/p\u003e\n\u003cp\u003eSpecific topics in the course include: \"Big-oh\" notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), randomized algorithms (QuickSort, contractio"])</script><script>self.__next_f.push([1,"n algorithm for min cuts), data structures (heaps, balanced search trees, hash tables, bloom filters), graph primitives (applications of BFS and DFS, connectivity, shortest paths).\u003c/p\u003e\n\u003cp\u003eLearners will practice and master the fundamentals of algorithms through several types of assessments. There are 6 multiple choice quizzes to test your understanding of the most important concepts. There are also 6 programming assignments, where you implement one of the algorithms covered in lecture in a programming language of your choosing. The course concludes with a multiple-choice final. There are no assignment due dates and you can work through the course materials and assignments at your own pace.\u003c/p\u003e2fb:T416,\u003cp\u003e\u003cem\u003ePlease Note: Learners who successfully complete this IBM course can earn a skill badge — a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in this course. Enroll to learn more, complete the course and claim your badge!\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn this course, you will learn what AI is and understand its applications and use cases and how it is transforming our lives. You will explore basic AI concepts including machine learning, deep learning, and neural networks as well as use cases and applications of AI. You will be exposed to concerns surrounding AI, including ethics, bias, jobs and the impacts on society.\u003c/p\u003e\n\u003cp\u003eYou will take a glimpse of the future with AI, get advice for starting an AI related career, and wrap up the course by demonstrating AI in action with a mini project.\u003c/p\u003e\n\u003cp\u003eThis AI for Everyone course does not require any programming or computer science expertise and is designed to introduce the basics of AI to anyone whether you have a technical background or not.\u003c/p\u003e2fc:T8c0,"])</script><script>self.__next_f.push([1,"\u003cp\u003e\u003cstrong\u003eAbout the Database Series of Courses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\"Databases\" was one of Stanford's three inaugural massive open online courses in the fall of 2011. It has been offered in synchronous and then in self-paced versions on a variety of platforms continuously since 2011. The material is now being offered as a set of five self-paced courses, which can be taken in a variety of ways to learn about different aspects of databases. \u003c/p\u003e\n\u003cp\u003e\u003cem\u003eRelational Databases and SQL\u003c/em\u003e is the most popular course in the Databases series. It is applicable to learners seeking to gain a strong understanding of relational databases, and to master SQL, the long-accepted standard query language for relational database systems. Additional courses focus on advanced concepts in relational databases and SQL, formal foundations and database design methodologies, and semistructured data.\u003c/p\u003e\n\u003cp\u003eAll of the courses are based around video lectures and demos. Many of them include quizzes between video segments to check understanding, in-depth standalone quizzes, and/or a variety of automatically-checked interactive exercises. Each course also includes an unmoderated discussion forum and pointers to readings and resources. The courses are described briefly below. Taught by Professor Jennifer Widom, the overall curriculum draws from Stanford's popular longstanding Databases course.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhy Learn About Databases\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDatabases are incredibly prevalent -- they underlie technology used by most people every day if not every hour. Databases reside behind a huge number of websites; they're a crucial component of telecommunications systems, banking systems, video games, and just about any other software system or electronic device that maintains some amount of persistent information. In addition to persistence, database systems provide a number of other properties that make them exceptionally useful and convenient: reliability, efficiency, scalability, concurrency control, data abstractions, and high-level query languages. Databases are so ubiquitous and important that computer science graduates frequently cite their database class as the one most useful to them in their industry or graduate-school careers.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"2fd:T805,"])</script><script>self.__next_f.push([1,"\u003cp\u003eStanford's online offering in Databases is now available as a set of five self-paced courses:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDatabases: Relational Databases and SQL\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eIntroduction to the relational model and concepts in relational databases and relational database management systems\u003c/li\u003e\n\u003cli\u003eComprehensive coverage of SQL, the long-accepted standard query language for relational database management systems\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eDatabases: Advanced Topics in SQL (prerequisite: Relational Databases and SQL)\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eCreating indexes for increased query performance\u003c/li\u003e\n\u003cli\u003eUsing transactions for concurrency control and failure recovery\u003c/li\u003e\n\u003cli\u003eDatabase constraints: key, referential integrity, and \"check\" constraints\u003c/li\u003e\n\u003cli\u003eDatabase triggers\u003c/li\u003e\n\u003cli\u003eHow views are created, used, and updated in relational databases\u003c/li\u003e\n\u003cli\u003eAuthorization in relational databases\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eDatabases: OLAP and Recursion\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eStar schemas, the data cube concept, and On-Line Analytical Processing (OLAP) features in relational databases including the Cube and Rollup operators\u003c/li\u003e\n\u003cli\u003eThe SQL standard for queries over recursively-defined relations\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eDatabases: Modeling and Theory\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eRelational algebra – the algebraic query language that provides the formal foundations of SQL\u003c/li\u003e\n\u003cli\u003eDependency theory and normal forms in relational databases as the basis of schema design\u003c/li\u003e\n\u003cli\u003eThe data-modeling component of the Unified Modeling Language (UML), how UML diagrams are translated to relations\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eDatabases: Semistructured Data\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eThe XML model for semistructured and self-describing data, including DTDs and some features of XML Schema\u003c/li\u003e\n\u003cli\u003eThe JSON model for human-readable structured or semistructured data\u003c/li\u003e\n\u003cli\u003eThe XPath language for processing XML data, and many features of the more advanced XQuery language\u003c/li\u003e\n\u003cli\u003eAn introduction to the XSLT rule-based language for querying and transforming XML data\u003c/li\u003e\n\u003c/ul\u003e"])</script><script>self.__next_f.push([1,"2fe:T50d,\u003cp\u003eAn estimated 120 zettabytes of data are created each year—that’s 21 zeroes—including new data captured, copied, and consumed. With that number growing annually, the requirements for database infrastructure, architecture, and storage are evolving just as rapidly.\u003c/p\u003e\r\n \r\n\u003cp\u003eAccording to the U.S. Bureau of Labor Statistics, computer science for databases, including database administration, analysts, and architects, corresponds with these numbers with anticipated growth of 8% over the next 10 years, faster than the average for all occupations. To prepare yourself for a career in the industry, you must not only understand the basics of computer science, but also how to create relationships with the data being created or ingested.\u003c/p\u003e\r\n \r\n \r\n\u003cp\u003eUsing HarvardX’s most popular courses, CS50: Introduction to Computer Science as the foundation, learners explore how to think algorithmically and how to solve problems efficiently, using real-world data sets.You will build on those skills by developing the core competencies needed for database development and structures. By focusing on the primary database language of SQL, you will learn how to create data relationships, normalize data to decrease the potential for errors or redundancy, and automate and optimize searches.\u003c/p\u003e2ff:T63e,\u003cp\u003eビッグデータやAI，いま，そういった言葉が世の中に満ち溢れています。それは，いろいろなことが計算に載るようになって，ビッグデータの利用や，それを使ったAI技術が本格化してきたからです。こうした潮流の中心となる「計算」の活用法を開発してきたのがコンピュータサイエンスという分野です。このコースでは，そのコンピュータサイエンスのエッセンスを学びます。ごく基礎的・入門的なところからはじめ，最先端のコンピュータサイエンスを概観できるまでの素養を身に付けられます。超入門的プログラミングで「計算」の設計"])</script><script>self.__next_f.push([1,"法を体験しながら，コンピュータサイエンスの基礎を学びます。\u003c/p\u003e\n\u003cp\u003eBig data, data-mining, machine learning and AI are commonly used terms world-wide these days. We are now able to “compute” various things with computers, and it allows us to use big data and AI technology effectively. Computer Science is a field where the usage of computers and “computations” have continuously evolved.In this course, you will learn the essence of computer science. You will obtain an overview of cutting-edge computer science as well as learn the basics and introductory level knowledge of computer science, while experiencing, designing and writing your own simple programs. The video lectures in this course are delivered in Japanese and accompanied by Japanese transcripts. An English version of this course is also available on edX.\u003c/p\u003e300:T5fc,\u003cp\u003eThis course is a variant of HarvardUniversity's introduction to computer science, CS50, designed especially for lawyers (and law students). Whereas CS50 itself takes a bottom-up approach, emphasizing mastery of low-level concepts and implementation details thereof, this course takes a top-down approach, emphasizing mastery of high-level concepts and design decisions related thereto. Ultimately, it equips students with a deeper understanding of the legal implications of technological decisions made by clients. \u003c/p\u003e\n\u003cp\u003eThrough a mix of technical instruction and discussion of case studies, this course empowers students to be informed contributors to technology-driven conversations. In addition, it prepares students to formulate technology-informed legal arguments and opinions. Along the way, it equips students with hands-on experience with Python and SQL, languages via which they can mine data for answers themselves. \u003c/p\u003e\n\u003cp\u003eTopics include algorithms, cloud computing, databases, networking, privacy, programming, scalability, security, and more, with a particular emphasis on understanding how the work developers do and the technological solutions they employ ma"])</script><script>self.__next_f.push([1,"y impact clients. Students emerge from this course with first-hand appreciation of how it all works and all the more confident in the factors that should guide their decision-making. \u003c/p\u003e\n\u003cp\u003eKeywords:law firm, computer programming, programming skills, computer programmers, patent attorney, legal practice, legal services, legal education, patent law\u003c/p\u003e301:T473,\u003cp\u003eIn this computer science course, you will learn the basics of programming in the Java language, and cover topics relevant to the AP Computer Science A course and exam.\u003c/p\u003e\n\u003cp\u003eThis course will cover:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eclasses\u003c/li\u003e\n\u003cli\u003eobjects and object-oriented design\u003c/li\u003e\n\u003cli\u003efields and visibility\u003c/li\u003e\n\u003cli\u003econstructors, mutators and accessor methods\u003c/li\u003e\n\u003cli\u003eencapsulation\u003c/li\u003e\n\u003cli\u003einterfaces\u003c/li\u003e\n\u003cli\u003ethe List interface\u003c/li\u003e\n\u003cli\u003emethod overriding\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThis course is for anyone interested in taking a first-level computer-programming course, particularly those who attend a school that does not provide a similar class.\u003c/p\u003e\n\u003cp\u003eNo previous programming knowledge is needed, but it is recommended that learners be comfortable with the topics addressed in \u003ca href=\"https://www.edx.org/course/ap-computer-science-java-programming-purduex-cs180-1x\"\u003eAP Computer Science A: Java Programming\u003c/a\u003e and \u003ca href=\"www.edx.org/course/ap-computer-science-java-programming-purduex-cs180-2x#!\"\u003eAP Computer Science A: Java Programming Data Structures and Loops\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eWe are looking forward to helping you explore this exciting new world!\u003c/p\u003e302:T6eb,\u003cp\u003eDo you ever wish you could just try out a study programme for a day? \u003c/p\u003e\n\u003cp\u003eNo strings attached, no papers to write, no lectures to drive to – just become a master student for a few hours and see if you enjoy it? \u003c/p\u003e\n\u003cp\u003eLooks like you found the right course! This Try-It lecture lets you peek into the unique field of \u003cstrong\u003ePhilosophy and Computer Science\u003c/strong\u003e , a master’s degree offered by the \u003cstrong\u003eUniversity of Bayreuth\u003c/strong\u003e in Germany. \u003c/p\u003e\n\u003cp\u003eThe compact course is structured into seven parts, each one contai"])</script><script>self.__next_f.push([1,"ning a 10 - 20 minute long lecture video. Throughout these chapters, the faculty behind Philosophy \u0026amp; Computer Science share their invaluable insights with you, and offer a glimpse of the innovative research areas that you will be dealing with should you study at Bayreuth. \u003c/p\u003e\n\u003cp\u003eYou can complete the course at your own pace. There are no deadlines or exams involved - you can simply take a look at the structure and coontents of the study programme and see for yourself if Philosophy \u0026amp; Computer Science is a field that you would like to further explore. \u003c/p\u003e\n\u003cp\u003ePhilosophy \u0026amp; Computer Science is a unique field of study that deals with the moral and philosophical principles behind modern technology, computational systems and applications. In order to critically deal with the rapid technological changes in society, we are in need of critical and creative minds who are able to see modern issues within a broader context. \u003c/p\u003e\n\u003cp\u003eWant to find out more about the study programme? Take a look at the \u003cstrong\u003ePhilosophy \u0026amp; Computer Science website \u003c/strong\u003eto find out more about the programme, its structure, topics and how to apply. You can also take a look at the programme's \u003cstrong\u003etrailer on YouTube\u003c/strong\u003e.\u003c/p\u003e303:T764,\u003cp\u003eCSAP.1x covers the material of AP Computer Science A which is equivalent to a first-semester, college-level course in computer science. This highly interactive course will introduce students to the fundamental concepts of computer science. The course will be structured to encourage students to think computationally and enjoy problem solving. New York City’s companies, museums, art and architecture will be used as examples to emphasize the ubiquitous role of computing and programming concepts in the world around us.\u003c/p\u003e\n\u003cp\u003eThe course will delve into object- oriented problem solving and design using the Java programming language. Students will have access to practice problems that will help them learn to program without spending hours on finding and fixing syntax errors. These will include o"])</script><script>self.__next_f.push([1,"nline multiple-choice questions in the style of those on the AP exam, mixed-up code that the user drags into the correct order, fill in the blank code and audio tours of the code.\u003c/p\u003e\n\u003cp\u003eTopics include problem solving, programming design strategies and data structures, algorithms, role of computation in real-world applications like smart phones, google glass and robots. This material may be used for self-study and as a preview by students and teachers considering the September 2015 offering of the course. Video lectures for this course will be available in May 2015. Ancillary material including labs will be added over the Summer of 2015. All of the course will be available September 1, 2015\u003c/p\u003e\n\u003cp\u003eThis is a self-paced course - you may take CSAP.1x on your schedule.\u003c/p\u003e\n\u003cp\u003e\u003ca href=\"https://www.edx.org/high-school-initiative\"\u003eLearn more about our High School and AP* Exam Preparation Courses\u003c/a\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eAdvanced Placement and AP are registered trademarks of the College Board, which was not involved in the production of, and does not endorse, these offerings.\u003c/li\u003e\n\u003c/ul\u003e304:T658,\u003cp\u003eCSAP.1x covers the material of AP Computer Science A which is equivalent to a first-semester, college-level course in computer science. This highly interactive course will introduce students to the fundamental concepts of computer science. The course will be structured to encourage students to think computationally and enjoy problem solving. New York City’s companies, museums, art and architecture will be used as examples to emphasize the ubiquitous role of computing and programming concepts in the world around us.\u003c/p\u003e\n\u003cp\u003eThe course will delve into object- oriented problem solving and design using the Java programming language. Students will have access to practice problems that will help them learn to program without spending hours on finding and fixing syntax errors. These will include online multiple-choice questions in the style of those on the AP exam, mixed-up code that the user drags into the correct order, fill in the blank c"])</script><script>self.__next_f.push([1,"ode and audio tours of the code.\u003c/p\u003e\n\u003cp\u003eTopics include problem solving, programming design strategies and data structures, algorithms, role of computation in real-world applications like smart phones, google glass and robots. This material may be used for self-study and as a preview by students and teachers considering the September 2015 offering of the course.\u003c/p\u003e\n\u003cp\u003e\u003ca href=\"https://www.edx.org/high-school-initiative\"\u003eLearn more about our High School and AP* Exam Preparation Courses\u003c/a\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e*Advanced Placement and AP are registered trademarks of the College Board, which was not involved in the production of, and does not endorse, these offerings.\u003c/em\u003e\u003c/p\u003e305:T51e,\u003cp\u003eHow do computers work? What do computer scientists do? What does it take to make a computer or a computer program work? We answer these questions and more with MyCS: Computer Science for Beginners. \u003c/p\u003e\n\u003cp\u003eWe believe that anyone can succeed in and enjoy computer science. This course is an early introduction to CS, designed for anyone who's completely new to the field. It explores a combination of the basic principles of how computers work and how we can use them to solve interesting problems and create amazing things. Lessons alternate between general exercises and assignments in Scratch, which offer a chance to both practice some basic concepts of computer programming and explore the many cool, creative, and useful applications of CS. \u003c/p\u003e\n\u003cp\u003eYou don't need any CS or programming background to do this course - just a bit of basic math and a lot of creative thinking. The course is intended especially for middle school students and their teachers, but is good for learners of all ages. \u003c/p\u003e\n\u003cp\u003eThis material is based upon work supported by the National Science Foundation under Grant No. 1240939. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).\u003c/p\u003e306:T4f7,\u003cp\u003eWith more than 328 million terabytes of data "])</script><script>self.__next_f.push([1,"produced each day, the potential threat of security and data breaches worldwide is constantly looming. Considering more than 500 billion data records were compromised in 2023 alone, businesses and individuals grapple with the new reality that hacking and breaches are becoming more sophisticated by the minute.\u003c/p\u003e\r\n\r\n\u003cp\u003eIn this changing landscape, those who are well equipped to not only manage threats or compromised systems, but also anticipate and prevent such attacks, will position themselves and their organizations for long term success.\u003c/p\u003e\r\n\r\n\u003cp\u003eBy combining two of HarvardX’s most popular courses, CS50's Introduction to Computer Science and CS50's Introduction to Cybersecurity, learners will engage with a unique blend of programming skills, computer science fundamentals, and specialized insights into the world of cybersecurity.\u003c/p\u003e\r\n\r\n\u003cp\u003eRegister today to explore the convergence of data science and cybersecurity in this CS50 Professional Certificate Program, where you will understand the threats and opportunities in the cybersecurity space, gaining the ability to make timely decisions when facing risk, predict vulnerabilities, and enable preemptive measures to safeguard against looming threats.\u003c/p\u003e307:T839,"])</script><script>self.__next_f.push([1,"\u003cp\u003e\u003cb\u003eThis Xseries is only for students in high school.\u003c/b\u003e Students not in high school should register for \u003ca href=\"https://www.edx.org/course/cs50s-understanding-technology\"\u003eCS50T\u003c/a\u003e and \u003ca href=\"https://www.edx.org/course/cs50s-introduction-to-computer-science\"\u003e CS50x\u003c/a\u003e separately.\u003c/p\u003e\r\n\r\nThis is CS50 AP, Harvard University's introduction to the intellectual enterprises of computer science and the art of programming for students in high school, which satisfies the College Board's \u003ca href=\"https://apcentral.collegeboard.org/courses/ap-computer-science-principles\"\u003eAP Computer Science Principles\u003c/a\u003e (CSP) curriculum framework. Students in high school may receive AP credit for this course provided their school approves the credit and administers the College Board's \u003ca href=\"https://apcentral.collegeboard.org/courses/ap-computer-science-principles/exam\"\u003eCreate Performance Task\u003c/a\u003e by Friday, April 30, 2021, 11:59 PM Eastern Time, and \u003ca href=\"https://apcentral.collegeboard.org/courses/ap-computer-science-principles/exam\"\u003eEnd-of-Course Multiple-Choice Exam\u003c/a\u003e on Thursday, May 13, 2021, 8:00 AM local time. \u003cb\u003eStudents should make all such arrangements in advance with their school directly.\u003c/b\u003e Students who earn a satisfactory score on all problem sets and a final project are also eligible to receive a verified certificate from HarvardX.\u003c/p\u003e\r\n\r\n\u003cp\u003eAn entry-level course for students with no prior background, taught by \u003ca href=\"https://www.edx.org/bio/david-j-malan\"\u003e David J. Malan\u003c/a\u003e, CS50 AP teaches students how to think algorithmically and solve problems efficiently. Topics include abstraction, algorithms, data structures, encapsulation, resource management, security, and software engineering. Languages include C, Python, and SQL plus students’ choice of: HTML, CSS, and JavaScript (for web development); Java or Swift (for mobile app development); or Lua (for game development). Problem sets inspired by the arts, humanities, social sciences, and sciences. Course culminates in a final project.\u003c/p\u003e \r\n\r\n\u003cp\u003eCS50 itself is Harvard University's largest course on campus.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"308:T5d3,\u003cp\u003eThe volume of data generated daily is staggering—more than 2.5 quintillion bytes every day. As the data surge continues to grow exponentially, organizations and individuals alike need to understand how to process and analyze this information to create strategic advantage.\u003c/p\u003e\r\n\r\n\u003cp\u003eThe CS50 Professional Certificate Program: Computer Science for Data Science explores the limitless potential of computer science converging with the analytical power of R programming. Beginning with CS50: Introduction to Computer Science, learners will complete an intensive and comprehensive dive into the core concepts of computer science developed by renowned Harvard University Professor David J. Malan. The course will cover concepts like abstraction, algorithms, and data structures and management—serving as a foundation for how data is used to improve decision-making and critical thinking skills.\u003c/p\u003e\r\n\r\n\u003cp\u003eThrough CS50’s Introduction to Programming with R, you will elevate your skills as you discover the statistical power of R using real-world datasets to manipulate data, create colorful visualizations, and package and export R code for reproducibility.\u003c/p\u003e\r\n\r\n\u003cp\u003eWhether you're a data enthusiast, a seasoned computing professional, or interested in entering the fastest-growing industry, this professional certificate program unravels the complexities of today’s data landscape, equipping you with the skills needed to create efficient, accurate, and actionable data insights.\u003c/p\u003e309:T415,\u003cp\u003eThis is an introductory course to learn programming with Java designed to teach how to code good programs in Java, understanding “good” as both correct and efficient. Basic principles of software engineering will be introduced to make it easier for our future self and others to reuse code. Ethical issues and the intellectual property of our programs will also be addressed in the last part of this course. Examples and case studies will be provided, so that learners can implement simple but increasingly complex programs in Java."])</script><script>self.__next_f.push([1,"\u003c/p\u003e\n\u003cp\u003eEmphasis is put on immediate feedback and on having a fun experience. Programming knowledge is not only useful to be able to program today’s devices such as computers and smartphones. It also opens the door to computational thinking, i.e. the application of computing techniques to every-day processes.\u003c/p\u003e\n\u003cp\u003eThis course is designed taking into account the subset and recommendations of the College Board in order to prepare learners for the Advanced Placement (AP) Computer Science A exam..\u003c/p\u003e30a:T841,"])</script><script>self.__next_f.push([1,"\u003cp\u003eThe focus of this class is on the \u003cem\u003elanguage of first-order logic\u003c/em\u003e , a formally defined language that allows us to make precise and unambiguous statements about any subject of interest.\u003c/p\u003e\n\u003cp\u003eUsing the language of first-order logic we will investigate many foundational topics in logic. We will address such questions as what counts as a grammatical expression, and the circumstances under which it makes a claim about the world (whether it can be considered true or false, E.g. “the sky is brown”, as compared to “oh, my goodness!”).\u003c/p\u003e\n\u003cp\u003eFor expressions that do make claims — we call these \u003cem\u003esentences\u003c/em\u003e — we can further examine whether they are true or false in particular situations. “Aristotle is alive” is a sentence that was once true, but became false around 2000 years ago, and has remained false ever since.\u003c/p\u003e\n\u003cp\u003eThese questions fall into the study of \u003cem\u003esemantics\u003c/em\u003e , or meaning.\u003c/p\u003e\n\u003cp\u003eOnce we understand how sentences can be considered true or false, we can investigate important related questions. Some sentences are always true, that is true in every situation — we call such sentences \u003cem\u003elogical truths\u003c/em\u003e. Sentences bear relationships with one another. For example, two sentences might be true in exactly the same situations - they are \u003cem\u003elogically equivalent.\u003c/em\u003e We will demonstrate methods for determining when these properties and relationships hold as natural extensions to the semantic theory for first-order logic.\u003c/p\u003e\n\u003cp\u003eFinally, we will explore the limits of first-order logic. There are some sentences of English that are not expressible in the language, and it is important to know that this is the case, and to understand why it is so. This observation has led logicians to develop yet more powerful languages with more complex semantics. Almost all of these languages are based on the language of first-order logic and knowledge of first-order logic is fundamental to understanding them. So first-order logic is a basic building block for the study of these language and is a great place to begin the journey into the field of logic.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"30b:T7f9,\u003cp\u003eThis class is an introduction to one of the basic tools used in the study of logic, a tool that is applied in a range of disciplines from computer science and math to linguistics and philosophy.\u003c/p\u003e\n\u003cp\u003eThe course is divided into two halves. In the first we study a fragment of first-order logic called \u003cem\u003epropositional logic\u003c/em\u003e. This language allows us to get our feet wet with the basic ideas of the course. These ideas include the specification of formal grammar rules for determining when an expression is \u003cem\u003ewell-formed\u003c/em\u003e. Well-formed expressions may make claims about the world, that is they may be considered \u003cem\u003etrue\u003c/em\u003e or \u003cem\u003efalse\u003c/em\u003e. You will learn how to determine whether a sentence is true in a particular situation. With the basic ideas in hand, you will then learn how to recognize relationships between sentences, the most important of which is \u003cem\u003econsequence\u003c/em\u003e. One sentence is a consequence of another, or follows from another, if it is true whenever the other is.\u003c/p\u003e\n\u003cp\u003eAt the end of the section on propositional logic, we will demonstrate that its expressiveness is limited, and that any attempt to increase the expressiveness of the language requires fundamentally new expressive devices.\u003c/p\u003e\n\u003cp\u003eIn the second half of the course we expand the language of propositional language to the full language of first-order logic, providing the new semantic theory. Everything that you learned about propositional logic holds in the larger language, but new expressive abilities are added to the language. We again investigate concepts of grammaticality, truth and consequence for the larger language. We will see that as a consequence of increasing the expressiveness of the language, the required extension to the semantic theory is more complicated than the theory of propositional logic.\u003c/p\u003e\n\u003cp\u003eNonetheless, there are still sentences of English that are not expressible in first-order logic. We will conclude by describing these limitations, setting the stage for further learning in the field of logic.\u003c/"])</script><script>self.__next_f.push([1,"p\u003e30c:T5a5,\u003cp\u003eWelcome to the self paced course, \u003cem\u003eAlgorithms: Design and Analysis, Part 2\u003c/em\u003e! Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth. This course is an introduction to algorithms for learners with at least a little programming experience. The course is rigorous but emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details. After completing this course, you will have a greater mastery of algorithms than almost anyone without a graduate degree in the subject.\u003c/p\u003e\n\u003cp\u003eSpecific topics in Part 2 include: greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes), dynamic programming (knapsack, sequence alignment, optimal search trees, shortest paths), NP-completeness and what it means for the algorithm designer, analysis of heuristics, local search.\u003c/p\u003e\n\u003cp\u003eLearners will practice and master the fundamentals of algorithms through several types of assessments. There are 6 multiple-choice problem sets to test your understanding of the most important concepts. There are also 6 programming assignments, where you implement one of the algorithms covered in lecture in a programming language of your choosing. The course concludes with a multiple-choice final.\u003c/p\u003e\n\u003cp\u003eThere are no assignment due dates and you can work through the course materials and assignments at your own pace.\u003c/p\u003e30d:T504,\u003cp\u003eThis course is designed to show you how to teach computational thinking to children aged 7-12+. The course will be valuable to you, whether you are new to this approach or an enthusiastic practitioner. It offers ways to explore computational thinking using simple tools readily available in classrooms and homes, such as cards, chalk and scales to engage with students.\u003c/p\u003e\n\u003cp\u003eBased on the content in the popular open-source CS Unplugged website (csunplugged.org), this course demonstrates how to teach computational thinking from unplugged to plugging-it-in with programming. \u003c/p"])</script><script>self.__next_f.push([1,"\u003e\n\u003cp\u003eEach module will weave in the following: \u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eConnections to apply CS Unplugged into classroom programmes by structuring the modules to have suitable activities that lead on from each other.\u003c/li\u003e\n\u003cli\u003eAn explanation of why we value computational thinking in the classroom\u003c/li\u003e\n\u003cli\u003eWhat is the big picture around computational thinking (especially, what is computation, and how does it fit with all the definitions of computational thinking that teachers may encounter),\u003c/li\u003e\n\u003cli\u003eThe “so what” about each concept, how it connects to people, and where you see it in everyday life\u003c/li\u003e\n\u003cli\u003e\u003cspan lang=\"EN\"\u003eStories of history – human connections\u003c/span\u003e\u003cspan lang=\"EN\"\u003e\u003c/span\u003e\u003c/li\u003e\n\u003c/ul\u003e30e:T4d1,\u003cp\u003eThis course is designed for elementary and middle-school teachers or parents with no assumption of prior background in either coding or the Scratch programming environment. The course has three main goals: Teach Scratch, teach pedagogical approaches to teaching coding with Scratch, and get teachers intimately familiar with the curriculum Scratch Encore. \u003c/p\u003e\n\u003cp\u003eDuring this course, participants will transition between learning Scratch as a learner, going through the Scratch Encore curriculum. This curriculum begins with elementary concepts such as the Scratch development environment, sequence, events, and basic loops. It then moves to intermediate topics that allow programmers to coordinate more complicated actions (intermediate loops and synchronization).\u003c/p\u003e\n\u003cp\u003eAt the same time, we provide explicit instruction on how to run a classroom using Scratch (e.g. entering your students into your classrooms, setting up studios, and grading assignments) as well as pedagogical approaches to teaching Scratch.\u003c/p\u003e\n\u003cp\u003eBy the end of the course, participants should be able to confidently teach Scratch using either Scratch Encore or a different curriculum, or to work on independent projects with their students or children.\u003c/p\u003e30f:Ta17,"])</script><script>self.__next_f.push([1,"\u003cp\u003e\u003cstrong\u003e\u003cspan lang=\"EN-US\"\u003eIntro \u0026amp; Welcome\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cspan lang=\"EN-US\"\u003eInstructor Introduction\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003e\u003cspan lang=\"EN-US\"\u003eOverview of course\u003c/span\u003e\u003cul\u003e\n\u003cli\u003e\u003cspan lang=\"EN-US\"\u003eContent\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003e\u003cspan lang=\"EN-US\"\u003eStructure and Navigation\u003c/span\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cspan lang=\"EN-US\"\u003e\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cspan lang=\"EN-US\"\u003eModule 1: Nature of Computation\u003c/span\u003e\u003c/strong\u003e\u003cspan lang=\"EN-US\"\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eCore Idea: Throughout history humans have utilized various physical phenomena to perform computations\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cspan lang=\"EN-US\"\u003eThe history and evolution of computers\u003c/span\u003e\u003cul\u003e\n\u003cli\u003e\u003cspan lang=\"EN-US\"\u003eLooking at past inventions and investigating the underlying physical phenomena which allows them to function\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003e\u003cspan lang=\"EN-US\"\u003eEx:, Abacus, Sundial, Thermostat, Slide Rule\u003c/span\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cspan lang=\"EN-US\"\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cspan lang=\"EN-US\"\u003eModule 2: Classical Computing\u003c/span\u003e\u003c/strong\u003e\u003cspan lang=\"EN-US\"\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eCore Idea: Classical computers utilize electricity and bits to perform digital math and logic calculations in a general-purpose way\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cspan lang=\"EN-US\"\u003eRepresenting information as digital bits\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003e\u003cspan lang=\"EN-US\"\u003eUtilizing electricity and digital circuits to perform computation\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003e\u003cspan lang=\"EN-US\"\u003eTypes of problems and time differences needed to solve them\u003c/span\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cspan lang=\"EN-US\"\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cspan lang=\"EN-US\"\u003eModule 3: Quantum Phenomena\u003c/span\u003e\u003c/strong\u003e\u003cspan lang=\"EN-US\"\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eCore Idea: Identifying the features of quantum systems\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cspan lang=\"EN-US\"\u003eEvolution of the atomic model\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003e\u003cspan lang=\"EN-US\"\u003eUnderstanding wavefunctions, interference, superposition and entanglement in quantum systems\u003c/span\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cspan lang=\"EN-US\"\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cspan lang=\"EN-US\"\u003eModule 4: Quantum Computers\u003c/span\u003e\u003c/strong\u003e\u003cspan lang=\"EN-US\"\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eCore Idea: Quantum phenomena can be utilized for the purposes of computation\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cspan lang=\"EN-US\"\u003eHow quantum computers utilize quantum physics to solve problems\u003c/span\u003e\u003cul\u003e\n\u003cli\u003e\u003cspan lang=\"EN-US\"\u003eBloch Sphere\u003c/span\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003e\u003cspan lang=\"EN-US\"\u003eQuantum problems\u003c/span\u003e\u003cul\u003e\n\u003cli\u003e\u003cspan lang=\"EN-US\"\u003eWhat types of problems can quantum computers solve\u003c/span\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003e\u003cspan lang=\"EN-US\"\u003eQuantum Logic\u003c/span\u003e\u003cul\u003e\n\u003cli\u003e\u003cspan lang=\"EN-US\"\u003eHow quantum gates are formed, and how this can be used to solve computational problems\u003c/span\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003c/ul\u003e"])</script><script>self.__next_f.push([1,"310:T53a,\u003cp\u003e\u003cem\u003ePlease Note: Learners who successfully complete this IBM course can earn a skill badge — a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in this course. Enroll to learn more, complete the course and claim your badge!\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eComputer Vision is one of the most exciting fields in Machine Learning, computer science and AI. It has applications in many industries such as self-driving cars, robotics, augmented reality, face detection in law enforcement agencies.\u003c/p\u003e\n\u003cp\u003eIn this intro-level course, you will learn about computer vision and its various applications across many industries. As part of this course, you will utilize Python, Watson AI, and OpenCV to process images and interact with image classification models. You will also build, train, and test your own custom image classifiers.\u003c/p\u003e\n\u003cp\u003eThis is a hands-on course and involves several labs and exercises. All the labs will be performed in the Cloud and you will be provided access to a Cloud environment completely free of charge.\u003c/p\u003e\n\u003cp\u003eAt the end of the course, you will create your own computer vision web app and deploy it to the Cloud.\u003c/p\u003e\n\u003cp\u003eThis course does not require any prior Machine Learning or Computer Vision experience, however, some knowledge of Python programming language is necessary.\u003c/p\u003e311:T694,\u003cp\u003eEvery day, our computers and phones correct our spelling, curate our social media, or translate news articles for us. But have you ever wondered how these applications work on a basic level? It turns out that these are often really difficult tasks. The branch of computer science working on solutions is called Natural Language Processing – or NLP for short. At the end of this four-week course, you will be equipped with a solid understanding of how to work with text – that is, with written language. You’ll have the foundation to go forth and explore both traditional, time-tested approaches as well as the exciting, modern advanced approaches using deep learning. Putting all of "])</script><script>self.__next_f.push([1,"this together, you’ll extend your reach in NLP through two assignments: to create your own text classification application and a generative, text suggestion system, like autocomplete, two very practical NLP applications that all of us use everyday. \u003c/p\u003e\n\u003cp\u003eThe instructor team has over 30 years of experience with natural language processing. Min has led research on NLP at NUS for over 20 years and has a well-known track record of publishing research work in NLP, digital libraries and information retrieval. He has also been part of the executive board of the ACL, the premier organization supporting NLP research worldwide. Chris has published multiple papers in the area of social media and text analysis. At NUS, he now teaches natural language processing, text and data mining, and database systems to graduate and undergraduate students. Both Chris and Min have won awards for teaching at NUS and have received strong student feedback in their teaching of the NLP course at NUS.\u003c/p\u003e312:T4c9,\u003cul\u003e\n\u003cli\u003eLearn about qubits, which are the building blocks of quantum computing\u003c/li\u003e\n\u003cli\u003eUnderstand the ways in which quantum computing and mechanics is different from classical computing and mechanics\u003c/li\u003e\n\u003cli\u003eLearn about the various use cases of quantum computing (e.g., Quantum searching, Haber-Bosch process, Teleportation etc.)\u003c/li\u003e\n\u003cli\u003eGain an intuitive understanding into how a qubit works with the help of simulations to play with\u003c/li\u003e\n\u003cli\u003eLearn how quantum gates can be developed and develop them to solve problems\u003c/li\u003e\n\u003cli\u003eDelve into building quantum solutions from a computational perspective by understanding coding fundamentals and implementing them in Python\u003c/li\u003e\n\u003cli\u003eGain working experience in building quantum gates with Scratch, IBM Circuit Composer, and Qiskit\u003c/li\u003e\n\u003cli\u003eDelve into understanding qubit states and gate operations using mathematical notations\u003c/li\u003e\n\u003cli\u003eExtend their knowledge by briefly exploring advanced quantum circuits and algorithms (e.g., Dutsch-Josza algorithm)\u003c/li\u003e\n\u003cli\u003eUnderstand the environmental and socie"])</script><script>self.__next_f.push([1,"tal impact of quantum computing and its solutions\u003c/li\u003e\n\u003cli\u003eExplore secondary and post-secondary pathways as well as career opportunities in the quantum computing field\u003c/li\u003e\n\u003c/ul\u003e313:T110d,"])</script><script>self.__next_f.push([1,"\u003cp\u003eOur lives are full of combinations. Combinatorial mathematics is just the science to deal with combinations of discrete items. As an ancient field, the history of combinatorial mathematics can be traced back over 4000 years to the age of the Great Yu in ancient China. Today, combinatorial mathematics is regarded as the basis of computer science since the algorithms in programming heavily rely on the analysis of the discrete elements.\u003c/p\u003e\n\u003cp\u003eInstead of relying on the traditional mathematical \"theorem - proof\" format, this course demonstrates various principles in an intuitive manner with ancient stories, the scenes of movies and even a magic show. What you’ll learn:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eThe counting principles based on the basic operations “+”, “-”, “*”, “/”;\u003c/li\u003e\n\u003cli\u003eGenerating functions\u003c/li\u003e\n\u003cli\u003eRecurrent number serials such as Fibonacci number, Catalan number, and more\u003c/li\u003e\n\u003cli\u003ePigeon hole principles\u003c/li\u003e\n\u003cli\u003eInclusion and exclusion principles\u003c/li\u003e\n\u003cli\u003ePolya counting based on group theory\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThis course is based on a highly regarded on-campus Tsinghua class called Combinatorics, and is ideal for students who are interested in mathematics or computer science. Enroll today and learn the mathematical theory needed to solve the real-world problems!\u003c/p\u003e\n\u003cp\u003eEvery aspect of our lives is full of combinations, and combinatorics is the study of discrete things. As a subject with a long history, the development of combinatorics can be traced back to the era of Dayu 4,000 years ago. Nowadays, combinatorial mathematics has opened a new chapter with the development of computer science. Since the analysis and implementation of program algorithms are based on the analysis of discrete objects, combinatorial mathematics has developed into a basic theory of computer science.\u003c/p\u003e\n\u003cp\u003eThis course changes the \"theorem-proof\" model of previous mathematics teaching and leads everyone to gradually explore the source of knowledge from the shallower to the deeper. There are ancient stories, movie clips, and even magic to interpret mathematical concepts. These forms are designed to lead everyone to feel the beauty of mathematics. Specific teaching content includes:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eCounting rules based on four arithmetic operations;\u003c/li\u003e\n\u003cli\u003eparent function;\u003c/li\u003e\n\u003cli\u003eRecursive sequences, such as Fibonacci numbers, Cattelan numbers, etc.;\u003c/li\u003e\n\u003cli\u003epigeonhole principle;\u003c/li\u003e\n\u003cli\u003eInclusion-exclusion principle;\u003c/li\u003e\n\u003cli\u003ePolya's theorem based on group theory.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe content and outline of this course are mainly based on the excellent course \"Combinatorics\" of Tsinghua University. Through the study of this course, learners can have an in-depth understanding of the abstract theory and specific methods of counting, and thus deeply understand the role of combinatorial mathematics in promoting the development of computer theory. .\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFAQ\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eI don’t speak Chinese, can I learn the course?\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the materials are in English. Though the original video was recorded in Chinese, the course team record the corresponding dubbing in English. All the audio and subtitles are processed to fit the English dubbing as much as possible, so that you can enjoy this wonderful course in English.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhat are the textbook and the reference books for this course?\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is no textbook requirement for this course. The handouts distributed every week are critical. The following books are references\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eRichard A. Brualdi; Introductory Combinatorics (5th edition), Pearson, 2009\u003c/li\u003e\n\u003cli\u003eJ.H.van Lint and R.M. Wilson; A course in Combinatorics, Cambridge University Press, 2001\u003c/li\u003e\n\u003cli\u003eLu Kaicheng, \"Combinatorics\" fourth edition, Tsinghua University Press\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eWhat is the grading breakdown?\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e70% quizzes and exercises\u003c/li\u003e\n\u003cli\u003e30% final exam\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eHow can I get the certificate?\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIf your final score is no less than 60.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDo I need to know how to program to learn this class?\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot necessary. This course is a math course which is based on fundamental theory. But to help the students to have the intuitive feel of the effects of the theory, we also provide a code lib that you can compare different implementations by running different programs.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"314:T867,"])</script><script>self.__next_f.push([1,"\u003cp\u003eGeometry can be traced back to ancient Greece, but Computational Geometry evolved less than 40 years as a branch of computer science. The Computational Geometry taught in this course is derived from classical discrete/combinatorial geometry and modern computer science.\u003c/p\u003e\n\u003cp\u003eComputational Geometry first appeared on the horizon when M. I. Shamos presented his Ph.D. dissertation in 1978. Since then, this phrase has been used to refer to algorithmic study on discrete and combinatorial geometric structures and can also be regarded as the geometric version of Algorithm Design and Analysis. Computational Geometry is now considered the basis of robotics, computer aided design and manufacturing (CAM and CID), and geographic information systems (GIS).\u003c/p\u003e\n\u003cp\u003eAs we all know, the history of geometry can be traced back to at least the ancient Greek times, but different people have different understandings of \"computational geometry\". The computational geometry discussed in this course originates from the combination of classical discrete/combinatorial geometry and modern computer science. The doctoral thesis completed by MI Shamos in 1978 marked the birth of this branch of the discipline. Since then, \"computational geometry\" has often referred specifically to the study of algorithms for discrete and combinatorial geometric structures. In short, it can also be considered as the geometric version of algorithm design and analysis.\u003c/p\u003e\n\u003cp\u003eThe teaching objectives of this course are threefold:\u003c/p\u003e\n\u003cp\u003eFirst, an overall understanding of computational geometry theory. This understanding will provide you with a geometric perspective in future research work. \u003cbr /\u003e\nSecond, a comprehensive understanding of geometric problem solving paradigms and strategies, including incremental construction, plane scanning, divide and conquer, Layering, approximation and randomization, etc. \u003cbr /\u003e\nFinally, a thorough grasp of basic geometric structures and algorithms, including convex hull, polygon subdivision, Voronoi diagram, Delaunay triangulation, as well as geometric intersection, point location, range search, interception window query etc.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"315:T4d3,\u003cp\u003e“Although many of the programs designed to teach kids to code are very simplistic, many of them, like Scratch, are suitable for all ages. It doesn't matter how old you are…Get started with the basics of programming!” -Lifehacker\u003c/p\u003e\n\u003cp\u003eWant to learn computer programming, but unsure where to begin? This is the course for you! Scratch is the computer programming language that makes it easy and fun to create interactive stories, games and animations and share them online.\u003c/p\u003e\n\u003cp\u003eThis course is an introduction to computer science using the programming language Scratch, developed by MIT. Starting with the basics of using Scratch, the course will stretch your mind and challenge you. You will learn how to create amazing games, animated images and songs in just minutes with a simple “drag and drop” interface.\u003c/p\u003e\n\u003cp\u003eNo previous programming knowledge needed. Join us as you start your computer science journey.\u003c/p\u003e\n\u003cp\u003eThis material is based upon work supported by the National Science Foundation under Grant No. 1044106. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).\u003c/p\u003e316:T47d,\u003cul\u003e\u003cli\u003e\u003cspan data-sheets-userformat=\"[null,null,12929,[null,0],null,null,null,null,null,null,2,null,0,null,null,\u0026quot;arial,sans,sans-serif\u0026quot;,10]\" data-sheets-value=\"[null,2,\u0026quot;-How to create amazing games, animated images and songs in the Scratch Programming language, one of the friendliest programming languages ever created \\n-The skill of solving interesting problems and making cool things with the help of a computer\u0026quot;]\"\u003eHow to create amazing games, animated images and songs in the Scratch Programming language, one of the friendliest programming languages ever created\u003c/span\u003e\u003c/li\u003e\n\t\u003cli\u003e\u003cspan data-sheets-userformat=\"[null,null,12929,[null,0],null,null,null,null,null,null,2,null,0,null,null,\u0026quot;arial,sans,sans-serif\u0026quot;,10]\" data-sheets-value=\"[null,2,\u0026quot;-How to cre"])</script><script>self.__next_f.push([1,"ate amazing games, animated images and songs in the Scratch Programming language, one of the friendliest programming languages ever created \\n-The skill of solving interesting problems and making cool things with the help of a computer\u0026quot;]\"\u003eThe skill of solving interesting problems and making cool things with the help of a computer\u003c/span\u003e\u003c/li\u003e\n\u003c/ul\u003e317:T515,\u003cp\u003eLearn to use the open development tool, \u003cem\u003eApp Inventor,\u003c/em\u003e to program on Android devices. You will learn how to design and build mobile apps -- apps that are aware of their location, send and receive text messages, and give advice and directions. The only limit on the types of apps you will learn to build is your own imagination!\u003c/p\u003e\n\u003cp\u003eHowever, computer science is not just about coding and building apps. We will also learn some of the fundamental principles of computer science. We'll learn about the potential and the limitations of computing and coding. We'll learn how the Internet works and about the positive and negative aspects of computing in today's society, and much more!\u003c/p\u003e\n\u003cp\u003eFor these broader computing concepts we will work within an emerging curricular framework -- the Computer Science Principles (CSP). The CSP framework is being developed by leading computer science educators from around the country under the auspices of the College Board and with funding support of the National Science Foundation.\u003c/p\u003e\n\u003cp\u003eIn addition to programming and CSP the course is project-based and emphasizes writing, communication, and creativity. Multiple-choice questions, in the style that students can expect to encounter on the AP exam, will also be a key component of this course.\u003c/p\u003e318:T535,\u003cp\u003eWe will use the free and open tool, App Inventor for Android, to explore advanced topics in computer science.\u003c/p\u003e\n\u003cp\u003eYou’ll build an app a week, exploring such advanced topics as gameplay over a network, encryption, and more.\u003c/p\u003e\n\u003cp\u003eAt the end of the course, we’ll collectively decide on an app that we will build together. You will be able to build almost anything yo"])</script><script>self.__next_f.push([1,"u can imagine!\u003c/p\u003e\n\u003cp\u003eBecause computer science is not just about coding and building apps, we will also learn some of the fundamental principles of computer science. We'll explore the potential and the limitations of computing and coding. We'll learn how the Internet works and about the positive and negative aspects of computing in today's society.\u003c/p\u003e\n\u003cp\u003eFor these broader computing concepts we will work within an emerging curricular framework -- the Computer Science Principles (CSP). The CSP framework is being developed by leading computer science educators from around the country under the auspices of the College Board and with funding support of the National Science Foundation.\u003c/p\u003e\n\u003cp\u003eIn addition to programming and CSP, the course is project-based and emphasizes writing, communication, and creativity. Multiple-choice questions, in the style that students can expect to encounter on the AP exam, will also be a key component of this course.\u003c/p\u003e319:T44b,\u003cp\u003e“Autonomous Robots” is a unique MOOC. is a self-paced, hands-on course that teaches the essential ideas behind autonomous robots and drones. \u003c/p\u003e\n\u003cp\u003eNowadays, robots can be found everywhere and the part autonomous robots take in the industry is in constant growing.\u003c/p\u003e\n\u003cp\u003eIn this new MOOC, we are going to take you on a journey to the algorithms and ideas behind those robots.\u003c/p\u003e\n\u003cp\u003eWe will explore topics such as sensors and how to utilize the smart-phone for them, the concept of power and batteries in mobile robots, state machines for autonomous robots, control algorithms and mapping strategies.\u003c/p\u003e\n\u003cp\u003eSince it is an online course, we focus on the software/algorithmic aspect of the subject. How do we do it? We created just for this course, a great flying simulator framework (based on Microsoft AirSim) that enables students to test their algorithms in 'real' environments. \u003c/p\u003e\n\u003cp\u003eThe course contains 4 assignments. Completing these assignments will enhance the student understanding of the current software tools and algorithms in this fascinating subject - Auto"])</script><script>self.__next_f.push([1,"nomous robots.\u003c/p\u003e31a:T5c0,\u003cp\u003eThe courses in the XSeries are designed to help people with no prior exposure to computer science or programming learn to think computationally and write programs to tackle useful problems. Some of the people taking the two courses will use them as a stepping stone to more advanced computer science courses, but for many it will be their first and last computer science courses. Since these courses may be the only formal computer science courses many of the students take, we have chosen to focus on breadth rather than depth. The goal is to provide students with a brief introduction to many topics so they will have an idea of what is possible when they need to think about how to use computation to accomplish some goal later in their career. That said, they are not “computation appreciation” courses. They are challenging and rigorous courses in which the students spend a lot of time and effort learning to bend the computer to their will.\u003c/p\u003e\r\n\r\n\u003cp\u003eIntroduction to Computer Science and Programming Using Python covers the notion of computation, the Python programming language, some simple algorithms, testing and debugging, and informal introduction to algorithmic complexity, and some simple algorithms and data structures. Introduction to Computational Thinking and Data Science will teach you how to use computation to accomplish a variety of goals and provides you with a brief introduction to a variety of topics in computational problem solving.\u003c/p\u003e31b:T63f,\u003cp\u003e“Introduction to Computing in Python” is a series of courses built from Georgia Tech’s online for-credit version of CS1301: Introduction to Computing. The series is designed to take you from no computer science background whatsoever to proficiency in the basics of computing and programming, specifically in the popular programming language Python. Rated as one of the most in-demand and beginner-friendly programming languages, Python training will give you a solid foundation not only for Python code but for further studies in c"])</script><script>self.__next_f.push([1,"omputer science.\u003c/p\u003e\r\n\r\n\u003cp\u003eThe syllabus and course material has been used at Georgia Tech for its for-credit CS1301 class for over a year. Over 400 students on campus have completed this version of the course, and our analysis shows that they exit the course with the same learning outcomes as students taking the traditional on-campus version. This Professional Certificate uses the same instructional material and assessments as learning Python on campus, giving you a Georgia Tech-caliber introduction into the field of computing at your own pace.\u003c/p\u003e\r\n\r\n\u003cp\u003eThis Professional Certification course follows a unique design. Students will cover the general, fundamental principles of computer science—which are applicable to any programming language like javascript or R — and then rapidly transition to those same programming concepts in Python. Short videos (2-3 minutes each) are rapidly interleaved with live programming problems, real-world examples, and multiple-choice questions to give you constant feedback on your progress and understanding.\u003c/p\u003e31c:T468,\u003cp\u003eLearn by doing! Codio courses are designed to engage and excite learners. Instead of reading or watching a video, you’ll be asked to write and run code (don’t worry, we provide code snippets to help get you started!). Course materials are presented in smaller, easier-to-manage formats, making this an excellent course for learners with no prior programming experience.\u003c/p\u003e\r\n\r\n\u003cp\u003eThis program is intended for people without programming experience who seek to develop C++ programming skills and learn about the underlying computer science concepts that will allow them to pick up other programming languages quickly. In these three courses, you will cover everything from fundamentals to object-oriented design.\u003c/p\u003e \r\n\r\n\u003cp\u003eThese topics will help prepare you to write basic programs that help them automate repetitive tasks such as modifying large files; architect larger applications into readable, maintainable, and scale-able code bases; understand the fundamentals of com"])</script><script>self.__next_f.push([1,"puter science presented in C++ to ease learning of other programming languages; and develop a sense of comfort and confidence while programming.\u003c/p\u003e31d:T470,\u003cp\u003eLearn Java by doing! Codio courses are designed to engage and excite beginners. Instead of reading or watching a video, you’ll be asked to write and run code (don’t worry, we provide code snippets to help get you started!). Course materials are presented in smaller, easier-to-manage formats, making this an excellent course for learners with no prior programming experience.\u003c/p\u003e\r\n\r\n\u003cp\u003eThis program is intended for people without programming experience who seek to develop Java programming skills and learn about the underlying computer science concepts that will allow them to pick up other programming languages quickly. In these three courses, you will cover everything from fundamentals to object-oriented design.\u003c/p\u003e\r\n\r\n\u003cp\u003eThese topics will help prepare you to write basic programs that help them automate repetitive tasks such as modifying large files; architect larger applications into readable, maintainable, and scale-able code bases; understand the fundamentals of computer science presented in Java to ease learning of other programming languages; and develop a sense of comfort and confidence while programming.\u003c/p\u003e31e:T478,\u003cp\u003eLearn Python by doing! Codio courses are designed to engage and excite beginners. Instead of reading or watching a video, you’ll be asked to write and run code (don’t worry, we provide code snippets to help get you started!). Course materials are presented in smaller, easier-to-manage formats, making this an excellent course for learners with no prior programming experience.\u003c/p\u003e\r\n\r\n\u003cp\u003eThis program is intended for people without programming experience who seek to develop Python programming skills and learn about the underlying computer science concepts that will allow them to pick up other programming languages quickly. In these three courses, you will cover everything from fundamentals to object-oriented design.\u003c/p\u003e \r\n\r\n\u003cp\u003eThese"])</script><script>self.__next_f.push([1," topics will help prepare you to write basic programs that help them automate repetitive tasks such as modifying large files; architect larger applications into readable, maintainable, and scale-able code bases; understand the fundamentals of computer science presented in Python to ease learning of other programming languages; and develop a sense of comfort and confidence while programming.\u003c/p\u003e31f:T436,\u003cp\u003eThe course lectures will be presented in short videos. To help you master the material, there will be in-lecture questions to answer, quizzes, and two exams: a midterm and a final. There will also be homework in the form of exercises that ask you to show a sequence of logical steps needed to derive a specific result, such as the sequence of steps a type checker would perform to type check a piece of code, or the sequence of steps a parser would perform to parse an input string. This checking technology is the result of ongoing research at Stanford into developing innovative tools for education, and we're excited to be the first course ever to make it available to students.\u003c/p\u003e\n\u003cp\u003eAn optional course project is to write a complete compiler for COOL, the Classroom Object Oriented Language. COOL has the essential features of a realistic programming language, but is small and simple enough that it can be implemented in a few thousand lines of code. Students who choose to do the project can implement it in either C++ or Java.\u003c/p\u003e\n\u003cp\u003eI hope you enjoy the course!\u003c/p\u003e320:T59d,\u003cp\u003eCould we create an opponent that will always beat us in rock paper scissors? How could we educate youth about the climate crisis through a video game? Can a story be interactive? \u003c/p\u003e\n\u003cp\u003eThese are some of the questions that will guide your learning experience in Coding For Your Classroom 4-9! \u003c/p\u003e\n\u003cp\u003eThis course is designed for educators to learn about ways to teach computational thinking logic to their students through fun, hands-on activities. The goal is for teachers to feel more confident with coding concepts and activities and to be able to"])</script><script>self.__next_f.push([1," create their own. This course will explore what computational thinking is and why it is important to teach it and introduce it to students at a young age, so we have more diversity in our technology fields in the future. Educators will leave this course knowing that they will be able to incorporate coding and develop students’ digital literacy through minor changes in their classrooms. Additionally, we aim to break barriers that teachers may face in their classrooms by providing participants with resources that develop these skills without the use of technology. At the end of the course, you will be provided with enough resources to begin to bring coding into your classroom start to feel confident creating your own!\u003c/p\u003e\n\u003cp\u003eTeachers will explore a variety of web-based platforms throughout the course such as: Microsoft MakeCode Micro:bit, Scratch, Twinery, and more!\u003c/p\u003e321:T40d,\u003cul\u003e\n\u003cli\u003eWhat is Computational Thinking\u003c/li\u003e\n\u003cli\u003ePlaces we see and use computational thinking in our everyday lives.\u003c/li\u003e\n\u003cli\u003eCurriculum Connections\u003c/li\u003e\n\u003cli\u003eDiversity in Computer Science\u003c/li\u003e\n\u003cli\u003eIdentify cross curricular connections between computer science and other subject matter. \u003c/li\u003e\n\u003cli\u003eBecome familiar with computational thinking through interactive lessons and activities.\u003c/li\u003e\n\u003cli\u003eIndividually develop personal digital literacy; become more comfortable and confident individually in computational thinking. \u003c/li\u003e\n\u003cli\u003eBe able to inspire computational thinking in learners through collaborative and stimulating hands-on activities.\u003c/li\u003e\n\u003cli\u003eIncorporating general strategies for evaluating computational thinking activities.\u003c/li\u003e\n\u003cli\u003eUnderstanding that technology drives just about everything that defines modern society as we know it.\u003c/li\u003e\n\u003cli\u003eLearn some coding activities (both plugged \u0026amp; unplugged) for your 4-9 class\u003c/li\u003e\n\u003cli\u003eConstraints in teaching coding.\u003c/li\u003e\n\u003cli\u003eHow to implement all these in the classroom\u003c/li\u003e\n\u003c/ul\u003e322:T40e,\u003cul\u003e\n\u003cli\u003eWhat is Computational Thinking\u003c/li\u003e\n\u003cli\u003ePlaces we see and use computational thinking in our everyday "])</script><script>self.__next_f.push([1,"lives.\u003c/li\u003e\n\u003cli\u003eCurriculum Connections\u003c/li\u003e\n\u003cli\u003eDiversity in Computer Science\u003c/li\u003e\n\u003cli\u003eIdentify cross curricular connections between computer science and other subject matter. \u003c/li\u003e\n\u003cli\u003eBecome familiar with computational thinking through interactive lessons and activities.\u003c/li\u003e\n\u003cli\u003eIndividually develop personal digital literacy; become more comfortable and confident individually in computational thinking. \u003c/li\u003e\n\u003cli\u003eBe able to inspire computational thinking in learners through collaborative and stimulating hands-on activities. \u003c/li\u003e\n\u003cli\u003eIncorporating general strategies for evaluating computational thinking activities.\u003c/li\u003e\n\u003cli\u003eUnderstanding that technology drives just about everything that defines modern society as we know it.\u003c/li\u003e\n\u003cli\u003eLearn some coding activities (both plugged \u0026amp; unplugged) for your K-3 class\u003c/li\u003e\n\u003cli\u003eConstraints in teaching coding.\u003c/li\u003e\n\u003cli\u003eHow to implement all these in the classroom\u003c/li\u003e\n\u003c/ul\u003e323:T574,\u003cp\u003eThe demand for data scientists is projected to grow 10x faster than other occupations (Source: US Bureau of Labor Statistics). This IBM Data Science Professional Certificate gives you the job-ready skills and practical experience you need to start your career in data science and machine learning. No prior computer science or programming experience is required.\u003c/p\u003e\r\n\r\n\u003cp\u003eData scientists analyze and interpret complex, large datasets using data mining, machine learning, and predictive modeling techniques. They then seek to uncover patterns, trends, and insights that help businesses make informed decisions.\u003c/P\u003e\r\n\r\n\u003cp\u003eDuring this program, you’ll learn Python programming, SQL for database querying, data manipulation with Pandas and Numpy, data visualization with Matplotlib and Seaborn, and machine learning with Scikit-learn. You’ll work hands-on with data science tools like Jupyter Notebooks, RStudio, and IBM watsonx. You'll use GitHub for version control and access data sources with APIs. Plus, you’ll gain valuable practical skills through hands-on labs, course projects, and a capstone proj"])</script><script>self.__next_f.push([1,"ect you can put on your resume and talk about in interviews.\u003c/p\u003e\r\n\r\n\u003cp\u003eIf you’re looking to get started in data science, this program gives you the job-ready skills you need to catch the eye of an employer. Enroll today and look forward to kickstarting a highly rewarding career.\u003c/p\u003e324:T5f1,\u003cp\u003eThe world of Artificial Intelligence (AI) is no longer science fiction. Instead, it is rapidly permeating across all industries and impacting every aspect of our daily-life. Whether you are an industry professional, an executive, an entrepreneur or a student – developing a foundational understanding of AI and its impact on your organization and our society is of paramount importance and will transform your career.\u003c/p\u003e\r\n\r\n\u003cp\u003eThis program is meant for those with little or no background in AI, computer science, or data science and does not require any programming skills. Each course is designed to provide a relevant and applicable comprehension of the basic concepts of AI and its many applications and use cases across various industries. You will also be introduced to terms like machine learning, deep learning, neural networks and natural language processing.\u003c/p\u003e\r\n \r\n\u003cp\u003eAs you journey through the series you will also be introduced to IBM Watson AI services that enable any business to easily deploy pre-built AI smarts to across your business. When you are ready you can build up to more complex topics in our full 6-course Applied AI Professional Certificate program where you be able to develop and deploy AI powered applications.\u003c/p\u003e\r\n \r\n\u003cp\u003eThrough hands-on interactions with several AI environments and applications you will also learn about creating intelligent virtual assistants and how they can be leveraged in different scenarios in your current job or as a way to jumpstart your next career.\u003c/p\u003e325:T542,\u003cp\u003eData science and machine learning skills continue to be in highest demand across industries, and the need for data practitioners is booming. Upon completing this Professional Certificate program, you will be armed with th"])</script><script>self.__next_f.push([1,"e basics to jump start your career in data science and machine learning.\u003c/p\u003e\r\n\r\n\u003cp\u003eIt is a myth that to become a data scientist you need a Ph.D. This Professional Certificate is suitable for anyone who has some computer skills and a passion for self-learning. No prior computer science or programming knowledge is necessary. Anyone with some computer skills and a passion for self-learning can succeed as we start small and build up to more complex problems and topics.\u003c/p\u003e\r\n \r\n\u003cp\u003eWhen you are ready you can build up to more complex topics in our full 9-course Data Science Professional Certificate program which covers a wide array of data science topics including: open source tools and libraries, methodologies, Python, databases, SQL, data visualization, data analysis, machine learning, and a capstone project.\u003c/p\u003e\r\n \r\n\u003cp\u003eWith the tremendous need for data science and data analyst professionals in the market today, this program will kick-start your path in data science and arm you with the fundamentals of Data Science so that you have the confidence to take the plunge and start your data science career today.\u003c/p\u003e326:T79e,\u003cp\u003eWant to learn about circuits and electronics? Wondering how the electronics behind sensors and actuators works, or how to make computers run faster, or your mobile phone battery last longer? This series of circuits and electronics courses taught by edX CEO and MIT Professor Anant Agarwal and colleagues is for you. \u003c/p\u003e\r\n\r\n\u003cp\u003eThese online Circuits \u0026 Electronics courses are taken by all MIT Electrical Engineering and Computer Science (EECS) majors.\u003c/p\u003e\r\n\r\n\u003cp\u003eTopics covered include: circuit abstraction, circuit elements such as resistors and sources, signals, and networks; circuit design and circuit analysis methods; digital abstraction, digital logic, and basic digital design; electronic devices including MOSFETs, digital switches, amplifiers; Energy storage elements like capacitors and inductors; dynamics of first-order and second-order networks and circuit speed; design in the time and frequency domai"])</script><script>self.__next_f.push([1,"ns; op-amps, filters, and analog and digital circuits, signal processing, and applications. Design and lab exercises are also significant components of the XSeries program.\u003c/p\u003e\r\n\r\n\u003cp\u003eWeekly coursework includes interactive video sequences, readings from the textbook, homework, fun online laboratories, and optional tutorials. Each course will also have a final exam. \u003c/p\u003e\r\n\r\n\u003cp\u003eThese are self-paced courses, so there are no weekly deadlines. \u003cbr\u003e\u003cbr\u003e\u003c/p\u003e\r\n\r\n\u003ch3\u003eStudent Testimonials\u003c/h3\u003e\r\n\u003cp style=\"margin-left:3%;\"\u003e\u003ci\u003e“Brilliant course! It's definitely the best introduction to electronics in Universe! Interesting material, clean explanations, well prepared quizzes, challenging homeworks and fun labs.” \u003c/i\u003e- Ilya\u003cbr\u003e\r\n\u003cbr\u003e\r\n\u003ci\u003e“6.002x will be a classic in the field of online learning. It combines Prof. Agarwal's enthusiasm for electronics and education. The online circuit design program works very well. The material is difficult. I took the knowledge from the class and built an electronic cat feeder.” \u003c/i\u003e- Stan\u003c/p\u003e327:Ta57,"])</script><script>self.__next_f.push([1,"\u003cp\u003eIn this exciting Professional Certificate program offered by Harvard University and Google TensorFlow, you will learn about the emerging field of Tiny Machine Learning (TinyML), its real-world applications, and the future possibilities of this transformative technology.\u003c/p\u003e\r\n\r\n\u003cp\u003eTinyML is a cutting-edge field that brings the transformative power of machine learning (ML) to the performance- and power-constrained domain of tiny devices and embedded systems. Successful deployment in this field requires intimate knowledge of applications, algorithms, hardware, and software.\u003c/p\u003e\r\n\r\n\u003cp\u003eThis first course in this series, Fundamentals of TinyML, will teach you the fundamentals of machine and deep learning. In this course, you will understand the language of tiny machine learning, which goes beyond the traditional machine learning toolkit due to the energy and memory constraints of tiny devices. The second course, Applications of TinyML, dives into an array of applications, where you will see how tools like voice recognition works in practice on small devices and you can see and implement common algorithms such as neural networks.\u003c/p\u003e\r\n\r\n\u003cp\u003eThe third course, Deploying TinyML, will give you a chance to use an open source hardware and prototyping platform to build your own tiny device. Featuring projects based on an Arduino board—TinyML Program Kit—the program emphasizes hands-on experience with training and deploying machine learning into tiny embedded devices. The TinyML Program Kit has everything you need to unlock your imagination and build applications around image recognition, audio processing, and gesture detection. Before you know it, you’ll be implementing an entire tiny machine learning application.\u003c/p\u003e\r\n\r\n\u003cp\u003eThroughout the series, you will learn how the Python programming language using TensorFlow (Lite/Micro) is used to power these devices as well as important topics in the responsible design of Artificial Intelligence systems. These first-of-their-kind online courses combine data science, computer science, and engineering to feature real-world application case studies that examine the challenges facing TinyML deployments.\u003c/p\u003e\r\n\r\n\u003cp\u003eThis program is a collaboration between expert faculty at Harvard’s John A. Paulson School of Engineering and Applied Sciences (SEAS) and innovative members of Google’s TensorFlow team. Taught by Harvard Professor Vijay Janapa Reddi, Lead AI Advocate at Google, Laurence Moroney, and Technical Lead of Google’s TensorFlow and Micro team, Pete Warden, this course offers you the unique opportunity to learn from leaders in the AI and machine learning space.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"328:Tca2,"])</script><script>self.__next_f.push([1,"\u003cp\u003eEC-Council’s Essentials Series is a Cybersecurity certificate series covering essential skills in network defense, ethical hacking, and digital forensics. The Network Defense Essentials (N|DE), Ethical Hacking Essentials (E|HE), and Digital Forensics Essentials (D|FE) are 3 foundational, industry recognized Cybersecurity certification programs, that help students and early career professionals learn real-world skills required in today’s entry-level cybersecurity field. The Essentials Series was designed to educate cybersecurity beginners in a range of techniques and topics across industry verticals, such as securing local networks, combating cybercrime and cyber threats, mitigating network security breaches, ethical hacking, cyber-attacks from hackers, conducting forensic investigations, and more.\u003c/p\u003e\r\n\r\n\u003cp\u003eThe Essential Series includes three beginner level courses, each covering essential skills in Network Defense, Ethical Hacking, and Digital Forensics. This course series is designed for today's entry-level careers in information security, network defense, and digital forensics and is ideal for computer science and computer network learners aspiring to pursue a career in cybersecurity.\u003c/p\u003e\r\n\r\n\u003cp\u003eAll 3 Essentials Series courses are closely aligned to specific work roles within the National Initiative of Cybersecurity Education (NICE) framework. In result, students taking Essentials Series courses should be able to clearly determine which work roles in today’s industry they are prepared for with each cybersecurity certification.\u003c/p\u003e\r\n\r\n\u003cp\u003eEach course offers an industry certification exam. Exams for each course are 2 hours and consist of 75 multiple choice questions.\u003c/p\u003e\r\n\r\n\u003cp\u003e\u003cb\u003eNetwork Defense Essentials\u003c/p\u003e\u003c/b\u003e\r\n\r\n\u003cp\u003eNetwork Defense Essentials covers the fundamental concepts of information security and network defense across operating systems, computer network, security breaches, and local networks. This introductory cybersecurity course is designed for today's entry-level information security or cybersecurity careers and is ideal for learners aspiring to pursue a career in cybersecurity.\u003c/p\u003e\r\n\r\n\u003cp\u003e\u003cb\u003eEthical Hacking Essentials\u003c/p\u003e\u003c/b\u003e\r\n\r\n\u003cp\u003eEthical Hacking Essentials is an introductory cybersecurity course that covers ethical hacking, penetration testing fundamentals and prepares learners for a career in cybersecurity. This course will introduce learners to cyberattacks and cyber threats, as well as security breaches, phishing, password cracking, web application attacks, IoT and OT attacks, cloud computing, pen testing fundamentals, and more.\u003c/p\u003e\r\n\r\n\u003cp\u003e\u003cb\u003eDigital Forensics Essentials\u003c/p\u003e\u003c/b\u003e\r\n\r\n\u003cp\u003eDigital Forensics Essentials helps learners increase their competency and expertise in digital forensics and cybercrime, thereby adding value to their workplace and employer. This course will introduce learners to Computer Forensics Fundamentals as well as the Computer Forensics Investigation Process. Plan to learn about Dark Web, Cyberattacks and threats, Windows, Linux, Malware Forensics, and so much more! The interactive labs component of this course ensures that learners receive the hands-on, practical experience required for a future in digital forensics.\u003c/p\u003e\r\n\r\n\u003cp\u003e"])</script><script>self.__next_f.push([1,"329:Tb41,"])</script><script>self.__next_f.push([1,"\u003cp\u003eGreat code has its foundation built upon data structures and algorithms. One must have a deep understanding of how data structures operate and designing efficient algorithms. Implementing algorithmic techniques that efficiently manipulate data structures is the essence of this program.\u003c/p\u003e \r\n\r\n\u003cp\u003eGeorgia Tech’s undergraduate computer science program is ranked #5 in U.S. The CS1332 for-credit course has been taught for years at Georgia Tech. Class Central has ranked the “Data Structures \u0026 Algorithms” series in GTx as one of the “Top 100 Most Popular Courses of 2021”, as well as, the #5 “Best Data Structures \u0026 Algorithms” course sequence in 2023.\u003c/p\u003e\r\n\r\n\u003cp\u003e\r\nThe Data Structures and Algorithms Professional Certificate from GTx is a four-course series covering the foundations of data structures, and designing efficient algorithms. The learner will examine and implement the principles of data storage in low-level data structures such as LinkedLists, Stacks and Queues. The learner will understand the significance of Abstract Data Types (ADTs). The fundamentals of recursion, edge cases, and algorithmic efficiency are emphasized throughout the four-course series. The series transitions from linear data structures to nonlinear data structures. The learner will explore Binary Search Trees (BSTs), HashMaps and Heaps. Implementations of the depth-first search (dfs) and breadth-first search (bfs) traversal algorithms are presented. Higher order data structures, like AVL and 2-4 trees, delves into self-balancing algorithmic techniques. Computer scientists must have a thorough understanding of time complexity in order to write efficient algorithms. The 3rd \u0026 4th courses focus on efficiency by first reviewing iterative sorting algorithms, bubble sort, and then implementing optimizations applied the sorting algorithm which improves performance. Divide and conquer algorithms, such as merge sort, quicksort and radix sort, are explained. The series wraps up with the graph ADT that utilizes many lower level data structures as auxiliary data storage in order to implement Dijkstra’s shortest path and Minimum Spanning Tree (MST) algorithms.\u003c/p\u003e\r\n\r\n\u003cp\u003eThe Professional Certificate for this program uses the same instructional materials and assessments as this on-campus accredited CS 1332 course, giving you a Georgia Tech-caliber learning experience with data structures \u0026 algorithms in computing. The Data Structures and Algorithms series of courses uses the Java object-oriented programming language which remains one of the most popular languages among software developers. Short (3-5 minute) videos and visualization exploratory labs are just part of the instructional tools used to deliver the content in this program. Students completing this program exit with the same learning outcomes as the traditional Georgia Tech on-campus course.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"32a:Tf07,"])</script><script>self.__next_f.push([1,"\u003cp\u003eThe emergence of advanced embedded systems applications powered by the Internet of Things (IoT), Machine Learning (ML) and Edge Computing is changing the way we collect and optimise the data gathered from the world around us.\u003c/p\u003e\r\n\r\n\u003cp\u003eWith the advent of ‘always-on’, mobile and powerful smart devices enabled by Arm’s rich ecosystem of technology partners, developers are now able to bring their applications closer to where data is being generated – that is closer to the user.\u003c/p\u003e\r\n\r\n\u003cp\u003eBy deploying the connectivity of IoT, and the insights enabled by ML and the ubiquity of Edge Computing, this data can be processed efficiently, and interpreted at speed and volume, to create new and innovative human experiences that benefit not only the individual user, but society as a whole.\u003c/p\u003e\r\n\r\n\u003cp\u003eThe Advanced Embedded Systems on Arm Professional Certificate will provide you with the key to unlock the potential of this exciting new technology in the world of computer science. With Gartner predicting that by 2025 75% of enterprise-generated data will be created and processed by Edge Computing solutions, skilled professionals in this area will be in high demand.\u003c/p\u003e\r\n\r\n\u003cp\u003eThese online courses are aimed at learners already familiar with the basic principles of embedded system design. If you’re looking to level up your skills in this area, then we recommend you start your learning journey by taking our Professional Certificate in Embedded Systems Essentials with Arm.\u003c/p\u003e\r\n\r\n\u003cp\u003eThe ST DISCO-L475E board used in this Program can be purchased directly from our technology partner STMicroelectronics: \u003ca href=\"https://www.st.com/content/st_com/en/campaigns/educationalplatforms/iot-arm-edx-edu.html\"\u003ehttps://www.st.com/content/st_com/en/campaigns/educationalplatforms/iot-arm-edx-edu.html\u003c/a\u003e\u003c/p\u003e\r\n\r\n\u003cp\u003eIn Part 1 of the Program, we’ll give you an overview of the fundamentals of IoT, but quickly move to practical projects that will teach you the essentials of building Arm-based IoT applications. This is the perfect gateway for beginners looking to enter the transformational world of IoT.\u003c/p\u003e\r\n\r\n\u003cp\u003eOur labs will teach you the basics of device management for IoT solutions - how to develop programs to control peripherals and sensors on a microcontroller and how to transmit this data to mobile and cloud-based applications using Bluetooth and Wi-Fi.\u003c/p\u003e\r\n\r\n\u003cp\u003eWe’ll also provide you with the social context behind the technology with video case studies that illustrate the global impact of IoT applications. \u003c/p\u003e\r\n\r\n\u003cp\u003ePart 2 of the Program will build upon the knowledge acquired in the first online course and combine this with new skills focusing on how to train machine learning models and implement them at the ‘Edge’ using industry relevant Arm-based microcontrollers. We’ll take you through the basics of AI, ML and ML at the Edge. We’ll then introduce you to the concept of datasets and how to train machine learning algorithms using tools like Anaconda and Python. We’ll then go on to explore advanced topics such as Artificial Neural Networks and Computer Vision.\u003c/p\u003e \r\n\r\n\u003cp\u003eAlong the way, our practical lab exercises will show you how you can address real-world design problems in deploying ML applications, such as speech and pattern recognition, as well as image processing, using actual sensor data obtained from the microcontroller. We’ll also introduce you to the open source TensorFlow Python library, which is useful in the training and inference of deep neural networks.\u003c/p\u003e\r\n\r\n\u003cp\u003eBy acquiring the essential skills required to successfully develop advanced embedded systems applications, you will have taken your next step in becoming a part of a vibrant community of innovators. Spark your potential and enroll in our Advanced Embedded Systems on Arm Professional Certificate today!\u003c/p\u003e"])</script><script>self.__next_f.push([1,"32b:Tc66,"])</script><script>self.__next_f.push([1,"\u003cb\u003e\u003cp\u003eEssential Math for AI:\u003c/b\u003e\u003c/br\u003e\r\nEssential Math for AI is the first course within the two-part bridge series designed to ensure learners possess the prerequisite skills for more advanced courses in the \u003ca href=\"https://ai.engineering.columbia.edu/\"\u003eAI Professional Certificate program\u003c/a\u003e. This course serves as a review and refresher of the key mathematical concepts - discrete math, calculus, linear algebra, and probability theory. It is not an in-depth exploration of these topics; instead, it will focus on concepts that have applications in various areas of artificial intelligence.\u003c/p\u003e\r\n\r\n\u003cp\u003eBy completing this course, you will be prepared to tackle advanced AI courses with confidence. This course is specifically crafted to bridge any gaps in mathematical knowledge, ensuring a robust understanding of fundamental concepts in math. Throughout this course, you will develop and refine essential skills and knowledge, recalling and articulating basic concepts in discrete math, calculus, linear algebra, and probability theory. Additionally, you will be able to apply the acquired knowledge to solve problems across various areas of artificial intelligence.\u003c/p\u003e\r\n\r\n\u003cp\u003eThis course is offered by Professor Daniel Bauer, a renowned Lecturer in the discipline of natural language processing in the department of computer science at Columbia Engineering, Columbia University. It offers a unique opportunity to learn from one of the top engineering schools, enhancing your credentials and positioning you for success in the rapidly evolving field of artificial intelligence.\u003c/p\u003e \r\n\r\n\u003cb\u003e\u003cp\u003eProgramming \u0026 Data Structures:\u003c/b\u003e\u003c/br\u003e\r\nProgramming \u0026 Data Structures is the second course within the two-part bridge series designed to ensure learners possess the prerequisite skills for more advanced courses in the \u003ca href=\"https://ai.engineering.columbia.edu/\"\u003eAI Professional Certificate program\u003c/a\u003e. This course serves as a review and refresher of the key concepts in programming and data structures, emphasizing their applications in various areas of artificial intelligence.\u003c/p\u003e \r\n\r\n\u003cp\u003eBy taking this course, you will develop fundamental programming skills and utilize built-in data structures and object-oriented programming concepts in Python for effective data manipulation and algorithm development. By the end of this course, you will be familiar with essential Python packages for data analysis, visualization, numeric computing, and machine learning. Additionally, you will be able to write and debug simple programs in Python, including using functions, object-oriented programming, and built-in data structures like lists and dictionaries. Finally, you will understand and use basic functionality in NumPy, Matplotlib, Sci-kit learn, and Pandas.\u003c/p\u003e\r\n\r\n\u003cp\u003eThis course is offered by Professor Daniel Bauer, a renowned Lecturer in the discipline of natural language processing in the department of computer science at Columbia Engineering, Columbia University. It offers a unique opportunity to learn from one of the top engineering schools, enhancing your credentials and positioning you for success in the rapidly evolving field of artificial intelligence.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"32c:T41d,The fundamental guidelines and heuristics of user interface design to inform the creation of strong user interfaces, from major principles like discoverability and affordances to frameworks like distributed cognition and task analysis.,The stages of the design life cycle, including needfinding and requirements gathering; individual and group brainstorming; low- to high-fidelity prototyping; and qualitative, quantitative, and heuristic evaluation of human-computer interfaces.,The power of human-computer interaction in the modern world and the role it can play in promoting equity, accessibility, and progress.,The application of modern development frameworks and theories like the Agile Method, Universal Design, Activity Theory, and Value-Sensitive Design to the creation of computational interfaces.,The state of the art in HCI, including emerging technologies like virtual reality, augmented reality, and wearable devices; new ideas like context-sensitive interfaces and social computing; and application areas like healthcare and cybersecurity.32d:Ta88,"])</script><script>self.__next_f.push([1,"\u003cp\u003eLearn the fundamentals of Human Computer Interaction in this four-course certificate.\u003c/p\u003e\r\n\r\n\u003cp\u003eThis course begins with an introduction to the field of Human-Computer Interaction as a whole and where it sits in the context of related and similar fields like Human Factors Engineering and User Experience Design. Here, you’ll learn just enough of the history of HCI to get started having real conversations about the field.\u003c/p\u003e\r\n\r\n\u003cp\u003eThen, you’ll learn the fundamental design principles of human-computer interaction. You’ll start with the fundamental feedback cycle that underlies all interactions between users and interfaces. With that in mind, you’ll then learn the design principles developed by visionaries in the field like Don Norman, Jakob Nielsen, Larry Constantine, and Lucy Lockwood. From there, you’ll move into more advanced theories of HCI, including situated action and distributed cognition, then conclude by looking at how interface design can impact social change.\u003c/p\u003e\r\n\r\n\u003cp\u003eAfter you’ve learned the fundamental principles and theories of HCI, you’ll move onto the design life cycle. The design life cycle covers how you iteratively gather requirements, brainstorm alternatives, prototype interfaces, and gather user feedback quickly to make fast progress in designing and improving user interfaces. You’ll cover the basics of how to develop a good survey, conduct an informative interview, and control for bias throughout your needfinding processes. You’ll then learn about running effective brainstorming sessions, and then prototyping at the just-right level of fidelity for your current confidence in your designs. Finally, you’ll learn how to evaluate those prototypes with real users, gathering their feedback for a new run through the design life cycle.\u003c/p\u003e\r\n\r\n\u003cp\u003eAfter that, we’ll briefly look at the current state of human-computer interaction, focusing on three areas: technologies like virtual and augmented reality, ideas like gesture- or touch-based interaction, and application areas like healthcare and security. In this exploration, we’ll rely heavily on cutting-edge papers and publications from the ever-changing field of HCI.\u003c/p\u003e\r\n\r\n\u003cp\u003eThen finally, we’ll recap the entire course contents, and tell you what to do next to further your HCI education: whether it’s pursuing a Master’s or PhD in the field, taking follow-up MOOCs, or beginning your own HCI research career.\u003c/p\u003e\r\n\r\n\u003cp\u003eThe material in this course is borrowed from Georgia Tech’s CS6750: Human-Computer Interaction, part of its online Master of Science in Computer Science program. You’ll watch the exact same lectures as students in the for-credit program.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"32e:T4b0,\u003cp\u003eThe Professional Certificate in 5G Networking has been designed to introduce learners to core concepts of 5G networking, while examining practical examples of its deployment across various industries.\u003c/p\u003e\r\n\r\n\u003cp\u003eIn 5G Essentials, learners explore how 5G has evolved from its predecessors – 3G and 4G. We also analyse key concepts in 5G radio, 5G spectrum sharing, end-to-end 5G network architecture, enhanced Mobile Broadband (eMBB), Mass Connectivity, and Ultra Reliable and Low Latency Communications (URLLC).\u003c/p\u003e\r\n\r\n\u003cp\u003eIn 5G Deployment, learners look at how 5G is deployed through 5G Radio Access Network (RAN) Virtualisation, network slicing, and Multi-Access Edge Computing (MEC) for disaggregated core in different industries, such as health care and mining.\u003c/p\u003e\r\n\r\n\u003cp\u003eThis program is suitable for learners who are new to or who are already working in the fields of telecommunications, computer science and engineering, and who have an interest in 5G networking. There are no prerequisites, but it is best suited to learners who have completed or are completing tertiary education. It is also recommended that learners undertake the 5G Essentials course before the 5G Deployment course.\u003c/p\u003e32f:T4a7,\u003cp\u003eThe role of robots in society keeps expanding and diversifying, bringing with it a host of issues surrounding the relationship between robots and humans. This introduction to Human–Robot Interaction (HRI) provides a broad overview of the multidisciplinary topics central to modern HRI research. Students and researchers from robotics, computer science, psychology, sociology, and design will find it a concise and accessible guide to the current state of the field. This certificate presents all the relevant background concepts; describing how robots work, how to design them, and how to evaluate their performance. We will cover important design decisions, such as the social robots’ level of anthropomorphism. Furthermore, we will work through several interaction modalities, such as spatial interaction, non-verbal inte"])</script><script>self.__next_f.push([1,"raction, verbal interaction and emotions. The role that robots may play in our society will be discussed and real world application areas, such as learning, healthcare, personal assistants, and transport will be investigated. Students will receive access to an open access textbook during the course and can subscribe to an active podcast for bonus content.\u003c/p\u003e330:T911,"])</script><script>self.__next_f.push([1,"\u003cp\u003eWorking with leading teachers and academics, Teaching with Physical Computing is brought to you by the Education team at Arm, the world’s leading semiconductor IP company. Arm-based microcontrollers are in billions of devices – from supercomputers, mobile phones and cars to small computers from partners such as Micro:bit, Raspberry Pi and Arduino.\u003c/p\u003e\r\n\r\n\u003cp\u003eWe work with schools and partners in supporting teaching communities of practice in STEM \u0026 Computer Science education with training and a range of free-to-access resources on arm.com/schools.\u003c/p\u003e\r\n\r\n\u003cp\u003eWhether you’re new to teaching Computing or a specialist Computer Science teacher, Teaching with Physical Computing will set you on the path to becoming an expert in delivering physical computing projects in the classroom.\u003c/p\u003e\r\n\r\n\u003cp\u003eThe Arm School Program’s suite of professional development courses introduces you to the world of Physical Computing and how to apply it through Project-Based Learning (PBL) in the classroom. We demonstrate how programmable physical computing devices, such as the Micro:bit, Raspberry Pi and Arduino, enable educators to apply a constructionist approach to computing education, focussing classroom learning experiences around real world problem-solving. Combining programming languages, computational thinking and design thinking to design and build solutions to real-world problems is an experience that can change your students’ perceptions of Computer Science. Whether you try it once a week or a few times each year, the combination of physical computing and PBL is a powerful tool in bringing Computing concepts to life. \u003c/p\u003e\r\n\r\n\u003cp\u003eIn this self-paced experience for beginners in PBL, the program will lead you towards mastering the topic: the pedagogy, its practical application and supporting educational theoretical principles. It also covers how to embed Project-Based Learning into your curriculum, as well as how to assess it effectively. By completing this program, you will acquire a comprehensive toolkit of concepts and techniques that you can apply with confidence in the classroom.\u003c/p\u003e\r\n\r\n\u003cp\u003eFor more teaching and learning resources from the Arm School Program, visit \u003ca href=\"https://www.arm.com/resources/education/schools/content\"\u003ehttps://www.arm.com/resources/education/schools/content\u003c/a\u003e\u003c/p\u003e"])</script><script>self.__next_f.push([1,"331:T7ef,\u003cp\u003eDeveloped by Blockchain at Berkeley and faculty from UC Berkeley's premier Computer Science department, the Blockchain Fundamentals Professional Certificate program is a comprehensive survey of core topics in cryptocurrency, including Bitcoin, and blockchain technology. This program will help you develop the critical skills needed to future-proof your career. \u003c/p\u003e\r\n\r\n\u003cp\u003eThe barrier of entry for the blockchain space can oftentimes seem rather high, especially since the concept of blockchain and the benefits it provides is not yet as widely understood as other innovations. In order to overcome this barrier, this program will explore the main ideas, technologies, and ecosystem surrounding blockchain technology from both technical and non-technical standpoints. This program will help you develop the intuition for thinking of blockchain systems. You will learn the key strengths and motivations of distributed ledger technology, and also be exposed to the underlying mechanisms by which they function. \u003c/p\u003e\r\n\r\n\u003cp\u003eUnderstanding blockchain architecture and the new paradigm of scalable, decentralized applications is imperative for future-proofing your career. Blockchain-related jobs are the second fastest growing in today’s labor market and opportunities are not limited to technical research or development positions; there is a need for project management, community support, law, design, and more.\u003c/p\u003e\r\n\r\n\u003cp\u003eThis program is accessible by anyone, with any background. Whether students are planning their next career move as a blockchain developer, crypto trader, data analyst, researcher, or consultant, or are just curious about this field, the Blockchain Fundamentals professional certificate is the best way to get up to speed on blockchain technology. \u003c/p\u003e\r\n\r\n\u003cp\u003eAfter taking Blockchain Fundamentals, students will have a deepened understanding of blockchain, which they can use to formulate their own informed blockchain mental models, hypotheses, and use cases -- imperative for understanding the industry.\u003c/p\u003e332:T4c8"])</script><script>self.__next_f.push([1,",\u003cp\u003eAn introduction to programming using Scratch, a visual programming language via which aspiring programmers can write code by dragging and dropping graphical blocks (that resemble puzzle pieces) instead of typing out text. Used at the start of Harvard College's introductory course in computer science, CS50, Scratch was designed at MIT's Media Lab, empowering students with no prior programming experience to design their own animations, games, interactive art, and stories. Using Scratch, this course introduces students to fundamentals of programming, found not only in Scratch itself but in traditional text-based languages (like Java and Python) as well. Topics include: functions, which are instructions that perform tasks; return values, which are results that functions provide; conditions, via which programs can decide whether or not to perform some action; loops, via which programs can take action again and again; variables, via which programs can remember information; and more. Ultimately, this course prepares students for subsequent courses in programming.\u003c/p\u003e\n\u003cp\u003eScratch is developed by the Lifelong Kindergarten Group at the MIT Media Lab. See \u003ca href=\"https://scratch.mit.edu/\"\u003escratch.mit.edu\u003c/a\u003e.\u003c/p\u003e333:T49d,\u003cp\u003eWant to learn about circuits and electronics, but unsure where to begin? Wondering how to make computers run faster or your mobile phone battery last longer? This free circuits course taught by edX CEO and MIT Professor Anant Agarwal and colleagues is for you. \u003c/p\u003e\n\u003cp\u003eThis is the first of three online Circuits \u0026amp; Electronics courses offered by Professor Anant Agarwal and colleagues at MIT, and is taken by all MIT Electrical Engineering and Computer Science (EECS) majors. \u003c/p\u003e\n\u003cp\u003eTopics covered include: resistive elements and networks; circuit analysis methods including KVL, KCL and the node method; independent and dependent sources; linearity, superposition, Thevenin \u0026amp; Norton methods; digital abstraction, combinational gates; and MOSFET switches and small signal analysis. Design and lab exerci"])</script><script>self.__next_f.push([1,"ses are also significant components of the course. \u003c/p\u003e\n\u003cp\u003eWeekly coursework includes interactive video sequences, readings from the textbook, homework, online laboratories, and optional tutorials. The course will also have a final exam. \u003c/p\u003e\n\u003cp\u003eThis is a self-paced course, so there are no weekly deadlines. However, all assignments are due when the course ends.\u003c/p\u003e334:Tab8,"])</script><script>self.__next_f.push([1,"\u003cp\u003e\u003cem\u003ePlease Note: Learners who successfully complete this IBM course can earn a skill badge — a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in this course. Enroll to learn more, complete the course and claim your badge!\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis course provides students with the basics required to create data visualizations and dashboards using both Microsoft Excel and IBM Cognos Analytics. You begin the process of telling a story about your data by creating several basic and advanced charts in Excel and learning how to add them to a digital dashboard. You then become familiar with IBM Cognos Analytics - a popular tool for data visualization and analytics – and learn how to use it to create interactive and informative dashboards. By completing this course, you will gain a basic understanding of using spreadsheets as a tool for data visualization. You will also gain the ability to create effective data visualizations, such as charts or graphs, and you will start to see how they can play a key role in the communication of your data analysis findings to interested parties. All of this can be accomplished without the need to write any code. By the end of this course you will be able to describe common dashboarding tools used by a data analyst, design and create a dashboard in a cloud platform, and begin to raise your level of confidence when creating intermediate level data visualizations.\u003c/p\u003e\n\u003cp\u003eThe emphasis is on applied learning and hands-on practice in this course, and with each hands-on lab, you will gain further experience in the creation of basic and advanced charts and the creation of digital dashboards using both Excel and Cognos Analytics. The final assignment project will allow you to apply these newly acquired skills to create and use data visualizations and add them to a digital dashboard to fulfil a business scenario.\u003c/p\u003e\n\u003cp\u003eThis course makes it simple to get started using Excel and Cognos Analytics to create data\u003cbr /\u003e\nvisualizations and dashboards to help tell a story about your data, and it does not require any previous data analysis or computer science\u003c/p\u003e\n\u003cp\u003eexperience. The course also does not require you to perform any software downloads or installations. All that is required is basic computer literacy, high-school level math, a device with a modern web browser, and the ability to use (or create) a Microsoft account to access Excel online at no-cost, and a basic understanding of Excel spreadsheets. Although the Excel hands-on labs steps are specifically related to using ‘Excel for the web’, if you already have the full desktop version of Excel, you should be able to use that to follow along quite easily with the labs.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"335:T8c0,"])</script><script>self.__next_f.push([1,"\u003cp\u003e\u003cstrong\u003eAbout the Database Series of Courses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\"Databases\" was one of Stanford's three inaugural massive open online courses in the fall of 2011. It has been offered in synchronous and then in self-paced versions on a variety of platforms continuously since 2011. The material is now being offered as a set of five self-paced courses, which can be taken in a variety of ways to learn about different aspects of databases. \u003c/p\u003e\n\u003cp\u003e\u003cem\u003eRelational Databases and SQL\u003c/em\u003e is the most popular course in the Databases series. It is applicable to learners seeking to gain a strong understanding of relational databases, and to master SQL, the long-accepted standard query language for relational database systems. Additional courses focus on advanced concepts in relational databases and SQL, formal foundations and database design methodologies, and semistructured data.\u003c/p\u003e\n\u003cp\u003eAll of the courses are based around video lectures and demos. Many of them include quizzes between video segments to check understanding, in-depth standalone quizzes, and/or a variety of automatically-checked interactive exercises. Each course also includes an unmoderated discussion forum and pointers to readings and resources. The courses are described briefly below. Taught by Professor Jennifer Widom, the overall curriculum draws from Stanford's popular longstanding Databases course.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhy Learn About Databases\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDatabases are incredibly prevalent -- they underlie technology used by most people every day if not every hour. Databases reside behind a huge number of websites; they're a crucial component of telecommunications systems, banking systems, video games, and just about any other software system or electronic device that maintains some amount of persistent information. In addition to persistence, database systems provide a number of other properties that make them exceptionally useful and convenient: reliability, efficiency, scalability, concurrency control, data abstractions, and high-level query languages. Databases are so ubiquitous and important that computer science graduates frequently cite their database class as the one most useful to them in their industry or graduate-school careers.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"336:T523,\u003cp\u003eThis course is one of five self-paced courses on the topic of Databases, originating as one of Stanford's three inaugural massive open online courses released in the fall of 2011. The original \"Databases\" courses are now all available on edx.org.\u003c/p\u003e\n\u003cp\u003eThis course is broad and practical, covering indexes, transactions, constraints, triggers, views, and authorization, all in the context of relational database systems and the SQL language. This course builds on concepts introduced in \u003cem\u003eDatabases: Relational Databases and SQL\u003c/em\u003e and is recommended for learners seeking to advance their understanding and use of relational databases.\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eThe Indexes and Transactions section of this course covers two important features of database systems from the application-builder's perspective: indexing for increased performance, and transactions for concurrency control and failure recovery.\u003c/li\u003e\n\u003cli\u003eThe Constraints and Triggers section of this course explains key, referential integrity, and \"check\" constraints, followed by comprehensive coverage of database triggers.\u003c/li\u003e\n\u003cli\u003eThe Views and Authorization section of this course provides extensive coverage of how database views can be created, used, and updated, and introduces standard techniques for authorization in relational databases.\u003c/li\u003e\n\u003c/ul\u003e337:T805,"])</script><script>self.__next_f.push([1,"\u003cp\u003eStanford's online offering in Databases is now available as a set of five self-paced courses:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDatabases: Relational Databases and SQL\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eIntroduction to the relational model and concepts in relational databases and relational database management systems\u003c/li\u003e\n\u003cli\u003eComprehensive coverage of SQL, the long-accepted standard query language for relational database management systems\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eDatabases: Advanced Topics in SQL (prerequisite: Relational Databases and SQL)\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eCreating indexes for increased query performance\u003c/li\u003e\n\u003cli\u003eUsing transactions for concurrency control and failure recovery\u003c/li\u003e\n\u003cli\u003eDatabase constraints: key, referential integrity, and \"check\" constraints\u003c/li\u003e\n\u003cli\u003eDatabase triggers\u003c/li\u003e\n\u003cli\u003eHow views are created, used, and updated in relational databases\u003c/li\u003e\n\u003cli\u003eAuthorization in relational databases\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eDatabases: OLAP and Recursion\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eStar schemas, the data cube concept, and On-Line Analytical Processing (OLAP) features in relational databases including the Cube and Rollup operators\u003c/li\u003e\n\u003cli\u003eThe SQL standard for queries over recursively-defined relations\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eDatabases: Modeling and Theory\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eRelational algebra – the algebraic query language that provides the formal foundations of SQL\u003c/li\u003e\n\u003cli\u003eDependency theory and normal forms in relational databases as the basis of schema design\u003c/li\u003e\n\u003cli\u003eThe data-modeling component of the Unified Modeling Language (UML), how UML diagrams are translated to relations\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eDatabases: Semistructured Data\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eThe XML model for semistructured and self-describing data, including DTDs and some features of XML Schema\u003c/li\u003e\n\u003cli\u003eThe JSON model for human-readable structured or semistructured data\u003c/li\u003e\n\u003cli\u003eThe XPath language for processing XML data, and many features of the more advanced XQuery language\u003c/li\u003e\n\u003cli\u003eAn introduction to the XSLT rule-based language for querying and transforming XML data\u003c/li\u003e\n\u003c/ul\u003e"])</script><script>self.__next_f.push([1,"338:T5cf,\u003cp\u003eHave you wanted to build a TinyML device? In Deploying TinyML, you will learn the software, write the code, and deploy the model to your own tiny microcontroller-based device. Before you know it, you’ll be implementing an entire TinyML application.\u003c/p\u003e\n\u003cp\u003eA one-of-a-kind course, Deploying TinyML is a mix of computer science and electrical engineering. Gain hands-on experience with embedded systems, machine learning training, and machine learning deployment using TensorFlow Lite for Microcontrollers, to make your own microcontroller operational for implementing applications such as voice recognition, sound detection, and gesture detection.\u003c/p\u003e\n\u003cp\u003eThe course features projects based on a \u003ca href=\"https://store.arduino.cc/usa/tiny-machine-learning-kit\"\u003eTinyML Program Kit\u003c/a\u003e that includes an Arduino board with onboard sensors and an ARM Cortex-M4 microcontroller. The kit has everything you need to build applications around image recognition, audio processing, and gesture detection. Before you know it, you’ll be implementing an entire tiny machine learning application. You can \u003ca href=\"https://store.arduino.cc/usa/tiny-machine-learning-kit\"\u003epreorder your Arduino kit here\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eTiny Machine Learning (TinyML) is one of the fastest-growing areas of deep learning and is rapidly becoming more accessible. The third course in the TinyML Professional Certificate program, Deploying TinyML provides hands-on experience with deploying TinyML to a physical device.\u003c/p\u003e339:T58b,\u003cp\u003eThis programming course takes a unique approach, as it focuses on learning a systematic programming method rather than a programming language. This practical approach will help you channel your creativity so that you can program well in any language. \u003c/p\u003e\r\n\u003cp\u003eThis course, part of the \u003ca href=\"https://www.edx.org/micromasters/ubcx-software-development\"\u003eSoftware Development MicroMasters Program\u003c/a\u003e, presents a core design method with a focus on numbers, strings, images and lists.\u003c/p\u003e\r\n\u003cp\u003eYou will learn techniques to:\u003c/p\u003e\r\n\u003cul\u003e\r\n\u003cli\u003eDev"])</script><script>self.__next_f.push([1,"elop program requirements\u003c/li\u003e\r\n\u003cli\u003eProduce programs with consistent structure that are easy to modify later\u003c/li\u003e\r\n\u003cli\u003eMake your programs more reliable by building tests as an integral part of the programming process.\u003c/li\u003e\r\n\u003c/ul\u003e\r\n\u003cp\u003eThis course concludes with the design of a simple interactive game.\u003c/p\u003e\r\n\u003cp\u003eLearners who enroll in the Verified track will receive staff grading for the course project and increased interaction with the instructor and staff.\u003c/p\u003e\r\n\u003chr /\u003e\r\n\u003cp\u003e\u003cstrong\u003eLearner Testimonial \u003c/strong\u003e\u003c/p\u003e\r\n\u003cp\u003e\u003cem\u003e\"I have taken and completed tens of MOOCs on programming and computer science, I have even been and I am currently a TA in some of these courses. Among them are a few that deserve without hesitation the highest rate. But if I had to choose only one at the top of them it would be these two courses on systematic program design.\"\u003c/em\u003e - edX Learner\u003c/p\u003e33a:T8c0,"])</script><script>self.__next_f.push([1,"\u003cp\u003e\u003cstrong\u003eAbout the Database Series of Courses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\"Databases\" was one of Stanford's three inaugural massive open online courses in the fall of 2011. It has been offered in synchronous and then in self-paced versions on a variety of platforms continuously since 2011. The material is now being offered as a set of five self-paced courses, which can be taken in a variety of ways to learn about different aspects of databases. \u003c/p\u003e\n\u003cp\u003e\u003cem\u003eRelational Databases and SQL\u003c/em\u003e is the most popular course in the Databases series. It is applicable to learners seeking to gain a strong understanding of relational databases, and to master SQL, the long-accepted standard query language for relational database systems. Additional courses focus on advanced concepts in relational databases and SQL, formal foundations and database design methodologies, and semistructured data.\u003c/p\u003e\n\u003cp\u003eAll of the courses are based around video lectures and demos. Many of them include quizzes between video segments to check understanding, in-depth standalone quizzes, and/or a variety of automatically-checked interactive exercises. Each course also includes an unmoderated discussion forum and pointers to readings and resources. The courses are described briefly below. Taught by Professor Jennifer Widom, the overall curriculum draws from Stanford's popular longstanding Databases course.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhy Learn About Databases\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDatabases are incredibly prevalent -- they underlie technology used by most people every day if not every hour. Databases reside behind a huge number of websites; they're a crucial component of telecommunications systems, banking systems, video games, and just about any other software system or electronic device that maintains some amount of persistent information. In addition to persistence, database systems provide a number of other properties that make them exceptionally useful and convenient: reliability, efficiency, scalability, concurrency control, data abstractions, and high-level query languages. Databases are so ubiquitous and important that computer science graduates frequently cite their database class as the one most useful to them in their industry or graduate-school careers.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"33b:T4f2,\u003cp\u003eThis course is one of five self-paced courses on the topic of Databases, originating as one of Stanford's three inaugural massive open online courses released in the fall of 2011. 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Wondering how energy storage elements like capacitors and inductors work, or how to make microchips run faster? This free circuits course taught by edX CEO and MIT Professor Anant Agarwal and colleagues is for you. \u003c/p\u003e\n\u003cp\u003eThis is the second of three online Circuits and Electronics courses and is taken by all MIT Electrical Engineering and Computer Science (EECS) majors. \u003c/p\u003e\n\u003cp\u003eTopics covered include: MOSFET large signal and small signal analysis; amplifiers; energy storage elements like capacitors and inductors; and dynamics of first-order networks and circuit speed. Design and lab exercises are also significant components of the course. \u003c/p\u003e\n\u003cp\u003eWeekly coursework includes interactive video sequences, readings from the textbook, homework, online laboratories, and optional tutorials. The course will also have a final exam. \u003c/p\u003e\n\u003cp\u003eThis is a self-paced course, so there are no weekly deadlines. However, all assignments are due when the course ends.\u003c/p\u003e33e:T692,\u003cp\u003eComplete your introductory knowledge of computer science with this final course on objects and algorithms. Now that you've learned about complex control structures and data structures, learn to develop programs that more intuitively leverage your natural understanding of problems through object-oriented programming. Then, learn to analyze the complexity and efficiency of these programs through algorithms. In addition, certify your broader knowledge of Introduction to Computing with a comprehensive exam. \u003c/p\u003e\n\u003cp\u003eBy the end of this course, you'll be able to write programs in Python that leverage your more natural understanding of data structures by creating objects to represent the structures you work with most often. For example, if you were creating a class roster application, you'll learn how to create an object representing a student's name, ID number, and attendance record. Then, you'll be able to create applications that leverage sorting and searching algorithms to sort that ros"])</script><script>self.__next_f.push([1,"ter alphabetically, search for a particular student, and evaluate the efficiency of both those operations. \u003c/p\u003e\n\u003cp\u003eStructurally, the course is comprised of several parts. Instruction is delivered via a series of short (2-3 minute) videos. In between those videos, you'll complete both multiple choice questions and coding problems to demonstrate your knowledge of the material that was just covered. These exercises count for 20% of your grade. Then, after each major chapter, you'll complete a problem set of collected, more challenging problems. These count for 40% of your grade. Finally, you'll complete a final course exam, which counts for the remaining 40% of your grade.\u003c/p\u003e33f:T90a,"])</script><script>self.__next_f.push([1,"\u003cp\u003eRobotics and AI are all around us and promise to revolutionize our daily lives. Autonomous vehicles have a huge potential to impact society in the near future, for example, by making owning private vehicles unnecessary!\u003c/p\u003e\n\u003cp\u003eHave you ever wondered how autonomous cars actually work?\u003c/p\u003e\n\u003cp\u003eWith this course, you will start from a box of parts and finish with a scaled self-driving car that drives autonomously in your living room. In the process, you will use state-of-the-art approaches, the latest software tools, and real hardware in an engaging hands-on learning experience.\u003c/p\u003e\n\u003cp\u003eSelf-driving cars with Duckietown is a practical introduction to vehicle autonomy. It explores real-world solutions to the theoretical challenges of autonomy, including their translation into algorithms and their deployment in simulation as well as on hardware.\u003c/p\u003e\n\u003cp\u003eUsing modern software architectures built with Python, Robot Operating System (ROS), and Docker, you will appreciate the complementary strengths of classical architectures and modern machine learning-based approaches. The scope of this introductory course is to go from zero to having a self-driving car safely driving in a Duckietown.\u003c/p\u003e\n\u003cp\u003eThis course is presented by Professors and Scientists who are passionate about robotics and accessible education. It uses the Duckietown robotic ecosystem, an open-source platform created at the MIT Computer Science and Artificial Intelligence Laboratory and now used by over 150 universities worldwide.\u003c/p\u003e\n\u003cp\u003eWe support a track for learners to deploy their solutions in a simulation environment, and an additional option for learners that want to engage in the challenging but rewarding, tangible, hands-on learning experience of making the theory come to life in the real world. 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You will learn about UML class diagrams and how they are used to map out the structure of a business domain by showing business objects, their attributes, and associations.\u003c/p\u003e\n\u003cp\u003eTaught by an instructor with decades of experience in requirements engineering and domain modelling, this course will equip you with the skill of in-depth understanding of a UML class diagram and will enable you to judge the functional fit of a UML class diagram as blueprint for the development of an enterprise information system.\u003c/p\u003e\n\u003cp\u003eThe Unified Modeling Language (UML) has become an in-demand skill in software development and engineering. In fact, some of today’s top jobs, i.e. business analysts, enterprise architects, but also developers, technical consultants and solutions architects, require UML knowledge. 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In other words, even without C++ or Python knowledge, the key takeaways can still be obtained.\u003c/p\u003e34d:T706,\u003cp\u003e\u003cspan lang=\"EN-US\"\u003eOur world is witnessing a revolutionary change in the way we perceive money and the way we conduct financial transactions. Numerous prominent cities around the world have adopted digital currency. But what is digital currency exactly? How does it function? And most importantly, how can we guarantee its security for global users?\u003c/span\u003e\u003cspan lang=\"EN-US\"\u003e\u003c/span\u003e\u003cspan lang=\"EN-US\"\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eWould Cryptocurrency, Central Bank Digital Currency (CBDC), and Stablecoins constitute the future of money? CBDC is the digital form of a country's central-bank-issued fiat currency; however, only eleven countries have adopted CBDCs to date. Why is CBDC significant, and what are the advantages and disadvantages of instituting a national digital currency? An important type of Stablecoins is privately issued digital currencies that are pegged to a fia"])</script><script>self.__next_f.push([1,"t currency (i.e. USD). Can Stablecoins and CBDCs coexist? Bitcoin, Ethereum, and a number of other cryptocurrencies use decentralized blockchain technology to process and record transactions in order to assure transaction immutability and traceability. But is blockchain technology essential for digital currencies? How can users' privacy be protected, and what technologies can be utilized to increase the safety of digital currency?\u003cspan lang=\"EN-US\"\u003e\u003c/span\u003e\u003cspan lang=\"EN-US\"\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eIn this course, you will learn from three prominent FinTech leaders and academics, including Professor SM Yiu of the HKU Department of Computer Science, Professor Douglas Arner of the HKU Department of Law, and Dr. John Yuen of the HKU Department of Computer Science, who will share some great insights on the e-Money and e-Payment technology infrastructures and regulatory landscape that are currently driving digital currency.\u003c/p\u003e34e:T8c0,"])</script><script>self.__next_f.push([1,"\u003cp\u003e\u003cstrong\u003eAbout the Database Series of Courses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\"Databases\" was one of Stanford's three inaugural massive open online courses in the fall of 2011. It has been offered in synchronous and then in self-paced versions on a variety of platforms continuously since 2011. The material is now being offered as a set of five self-paced courses, which can be taken in a variety of ways to learn about different aspects of databases. \u003c/p\u003e\n\u003cp\u003e\u003cem\u003eRelational Databases and SQL\u003c/em\u003e is the most popular course in the Databases series. It is applicable to learners seeking to gain a strong understanding of relational databases, and to master SQL, the long-accepted standard query language for relational database systems. Additional courses focus on advanced concepts in relational databases and SQL, formal foundations and database design methodologies, and semistructured data.\u003c/p\u003e\n\u003cp\u003eAll of the courses are based around video lectures and demos. Many of them include quizzes between video segments to check understanding, in-depth standalone quizzes, and/or a variety of automatically-checked interactive exercises. Each course also includes an unmoderated discussion forum and pointers to readings and resources. The courses are described briefly below. Taught by Professor Jennifer Widom, the overall curriculum draws from Stanford's popular longstanding Databases course.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhy Learn About Databases\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDatabases are incredibly prevalent -- they underlie technology used by most people every day if not every hour. Databases reside behind a huge number of websites; they're a crucial component of telecommunications systems, banking systems, video games, and just about any other software system or electronic device that maintains some amount of persistent information. In addition to persistence, database systems provide a number of other properties that make them exceptionally useful and convenient: reliability, efficiency, scalability, concurrency control, data abstractions, and high-level query languages. Databases are so ubiquitous and important that computer science graduates frequently cite their database class as the one most useful to them in their industry or graduate-school careers.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"34f:T805,"])</script><script>self.__next_f.push([1,"\u003cp\u003eStanford's online offering in Databases is now available as a set of five self-paced courses:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDatabases: Relational Databases and SQL\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eIntroduction to the relational model and concepts in relational databases and relational database management systems\u003c/li\u003e\n\u003cli\u003eComprehensive coverage of SQL, the long-accepted standard query language for relational database management systems\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eDatabases: Advanced Topics in SQL (prerequisite: Relational Databases and SQL)\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eCreating indexes for increased query performance\u003c/li\u003e\n\u003cli\u003eUsing transactions for concurrency control and failure recovery\u003c/li\u003e\n\u003cli\u003eDatabase constraints: key, referential integrity, and \"check\" constraints\u003c/li\u003e\n\u003cli\u003eDatabase triggers\u003c/li\u003e\n\u003cli\u003eHow views are created, used, and updated in relational databases\u003c/li\u003e\n\u003cli\u003eAuthorization in relational databases\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eDatabases: OLAP and Recursion\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eStar schemas, the data cube concept, and On-Line Analytical Processing (OLAP) features in relational databases including the Cube and Rollup operators\u003c/li\u003e\n\u003cli\u003eThe SQL standard for queries over recursively-defined relations\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eDatabases: Modeling and Theory\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eRelational algebra – the algebraic query language that provides the formal foundations of SQL\u003c/li\u003e\n\u003cli\u003eDependency theory and normal forms in relational databases as the basis of schema design\u003c/li\u003e\n\u003cli\u003eThe data-modeling component of the Unified Modeling Language (UML), how UML diagrams are translated to relations\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eDatabases: Semistructured Data\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eThe XML model for semistructured and self-describing data, including DTDs and some features of XML Schema\u003c/li\u003e\n\u003cli\u003eThe JSON model for human-readable structured or semistructured data\u003c/li\u003e\n\u003cli\u003eThe XPath language for processing XML data, and many features of the more advanced XQuery language\u003c/li\u003e\n\u003cli\u003eAn introduction to the XSLT rule-based language for querying and transforming XML data\u003c/li\u003e\n\u003c/ul\u003e"])</script><script>self.__next_f.push([1,"350:Tae6,"])</script><script>self.__next_f.push([1,"\u003cul\u003e\n\u003cli\u003e\u003cstrong\u003eArtificial Intelligence\u003c/strong\u003e is more than just a collection of brilliant, innovative methods to solve problems. \u003cbr /\u003e\nIf you are interested in \u003cstrong\u003emachine learning\u003c/strong\u003e or are planning to explore it, the course will make you see artificial learning in an entirely new way. You will know how to formulate optimal hypotheses for a learning task. And you will be able to analyze learning techniques such as clustering or neural networks as just ways of compressing information.\u003c/li\u003e\n\u003cli\u003eIf you are interested in \u003cstrong\u003ereasoning\u003c/strong\u003e , you will understand that reasoning by analogy, reasoning by induction, explaining, proving, etc. are all alike; they all amount to providing more compact descriptions of situations.\u003c/li\u003e\n\u003cli\u003eIf you are interested in \u003cstrong\u003emathematics\u003c/strong\u003e , you will be amazed at the fact that crucial notions such as probability and randomness can be redefined in terms of algorithmic information. You will also understand that there are theoretical limits to what artificial intelligence can do.\u003c/li\u003e\n\u003cli\u003eIf you are interested in \u003cstrong\u003ehuman intelligence\u003c/strong\u003e , you will find some intriguing results in this course. Thanks to algorithmic information, notions such as unexpectedness, interest and, to a certain extent, aesthetics, can be formally defined and computed, and this may change your views on what artificial intelligence can achieve in the future.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eHalf a century ago, three mathematicians made the same discovery independently. They understood that the concept of information belonged to computer science; that computer science could say what information means. \u003cstrong\u003eAlgorithmic Information Theory\u003c/strong\u003e was born.\u003c/p\u003e\n\u003cp\u003eAlgorithmic Information is \u003cstrong\u003ewhat is left when all redundancy has been removed\u003c/strong\u003e. This makes sense, as redundant content cannot add any useful information. Removing redundancy to extract meaningful information is something computer scientists are good at doing.\u003c/p\u003e\n\u003cp\u003eAlgorithmic information is a great conceptual tool. It describes what artificial intelligence actually \u003cstrong\u003edoes\u003c/strong\u003e , and what it \u003cstrong\u003eshould do\u003c/strong\u003e to make optimal choices. It also says what artificial intelligence \u003cstrong\u003ecan’t do\u003c/strong\u003e. Algorithmic information is an essential component in the theoretical foundations of AI.\u003c/p\u003e\n\u003cp\u003eKeywords: \u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cspan lang=\"EN-GB\"\u003eAlgorithmic information, Kolmogorov complexity, theoretical computer science, universal Turing machine, coding, compression, semantic distance, Zipf’s law, probability theory, algorithmic probability, computability, incomputability, random sequences, incompleteness theorem, machine learning, Occam's razor, minimum description length, induction, cognitive science, relevance.\u003c/span\u003e\u003c/em\u003e\u003c/p\u003e"])</script><script>self.__next_f.push([1,"351:T46a,\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eHow to measure information through compression\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eHow to compare algorithmic information with Shannon’s information\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eHow to detect languages through joint compression\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eHow to use the Web to compute meaning similarity\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eHow probability and randomness can be defined in purely algorithmic terms\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eHow algorithmic information sets limits to the power of AI (Gödel’s theorem)\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eA criterion to make optimal hypotheses in learning tasks\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eA method to solve analogies and detect anomalies\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eA new understanding of machine learning as a way to achieve compression\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eWhy unexpected means abnormally simple\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eWhy coincidences are unexpected\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eWhy subjective information and interest are due to complexity drop and why relevance, aesthetics, emotional intensity and humour rely on coding.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eCaveat:\u003c/strong\u003e This course DOES NOT address the notion of \"computational complexity\" which measures the speed of algorithms.\u003c/p\u003e352:T403,\u003cp\u003eQuantum computing is a fast-growing technology and semiconductor chips are one of the most promising platforms for quantum devices.\u003cbr /\u003e\nThe current bottleneck for scaling is the ability to control semiconductor computing chips quickly and efficiently. \u003c/p\u003e\n\u003cp\u003eThis course, aimed at students with experience equivalent to a master’s degree in physics, computer science or electrical engineering introduces hands-on machine learning examples for the application of machine learning in the field of semiconductor quantum devices. Examples include coarse tuning into the correct quantum dot regime, specific charge state tuning, fine tuning and unsupervised quantum dot data analysis. \u003c/p\u003e\n\u003cp\u003eAfter the completion of the course students will be able to\u003c/p\u003e\n\u003col\u003e\n\u003cli\u003eassess the suitability of machine learning for specific qubit tuning or control task and\u003c/li\u003e\n\u003cli\u003eimplement a machine learning prot"])</script><script>self.__next_f.push([1,"otype that is ready to be embedded into their experimental or theoretical quantum research and engineering workflow.\u003c/li\u003e\n\u003c/ol\u003e353:T80c,"])</script><script>self.__next_f.push([1,"\u003cp\u003eAs RISC-V has made it easier to bring up processor chipsets, the need for compiler engineers in the RISC-V ecosystem has increased. There is an implicit need for toolchain experts who can help RISC-V vendors gain an edge over competitors with their expertise in compilation technologies. Learning about internals of the toolchain, building and debugging RISC-V applications will allow you to work with thousands of companies that are building the latest hardware technologies.\u003c/p\u003e\n\u003cp\u003eThis course is designed for engineers working with RISC-V vendors who are designing their own architectures, and those using RISC-V development boards to build applications. It is also useful for RISC-V application developers looking to improve performance or reduce the code size of their applications, toolchain developers, compiler engineers/performance engineers, and computer science students aspiring to major in systems software.\u003c/p\u003e\n\u003cp\u003eThis course begins with an introduction to the compiler toolchain and concepts of cross-compilation. You will learn how to use popular compiler toolchains (both LLVM and GCC) to build RISC-V applications. You will also learn how to debug toolchain issues and what resources to consult when you need help. This course will help you optimize applications for code size or performance and gain an understanding of the demands of applications with instrumentation techniques.\u003c/p\u003e\n\u003cp\u003eThe course prepares you to apply to in-demand job opportunities like toolchain engineers or systems performance engineers as most large organizations have a difficult time finding engineers who are good with performance optimizations. This is a beginner-level course to get you started with optimizing data center applications and mobile applications for performance. It enables you to work in startups building RISC-V-based devices and IOT systems that are resource-constrained. The course will also help undergraduate students get started with compiler toolchains and equip them with skills to optimize applications using compiler technologies.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"354:T40d,\u003cp\u003eIn this computer science course, you will learn advanced concepts underpinning the design of today’s multicore-based computers. Additionally, you will learn how design decisions affect energy efficiency and performance.\u003c/p\u003e\n\u003cp\u003eOverall, topics include fundamentals on exploiting parallelism among instructions such as out-of-order execution, branch prediction, exception handling and advanced concepts of memory systems including prefetching and cache coherency. These concepts are fundamental for future computer systems to maximize compute efficiency.\u003c/p\u003e\n\u003cp\u003eYou will also engage with a community of learners with similar interests to share knowledge.\u003c/p\u003e\n\u003cp\u003eThe course is derived from Chalmers’s advanced graduate course in computer architecture. Prospective students should have a foundation in basic computer design, as offered by, for example, in “\u003ca href=\"https://www.edx.org/course/computer-system-design-improving-energy-chalmersx-chm007x\"\u003eComputer System Design - Improving Energy Efficiency and Performance\u003c/a\u003e.“\u003c/p\u003e355:T522,\u003cp\u003eThiscourse opens an in-depth discussion and creates a better understanding of the field of developmental cognitive robotics. This field takes direct inspiration from child psychology theories and findings to develop sensorimotor and cognitive skills in robots. \u003c/p\u003e\n\u003cp\u003eCoursework will explore the principles of developmental robotics and will review the application of robotics models and techniques. The areas covered range from intrinsic motivation to motor and perceptual learning, social interaction, language learning, and abstract knowledge. \u003c/p\u003e\n\u003cp\u003eThe course will also explicitly discuss core theories and findings from developmental psychology and neuroscience that have directly inspired developmental robotics models. It will introduce students to the main concepts in robotics technology and the main robot platforms and simulators used in developmental robotics. \u003c/p\u003e\n\u003cp\u003eThecourse is suitable both for robotics and computer science students, as well as cognitive scientists and"])</script><script>self.__next_f.push([1," psychologists interested in computational models of cognition and behavior. It is also an option in the final year of a BSc/MSc degree in robotics, computer science, as well as for degree courses in psychology, anthropology, cognitive sciences. Part of the course has been created with Professor Matthew Schlesinger.\u003c/p\u003e356:Tba7,"])</script><script>self.__next_f.push([1,"\u003cp\u003eThis course takes you through lessons 14 through 18 of CS6750: Human-Computer Interaction as taught in the Georgia Tech Online Master of Science in Computer Science program. \u003c/p\u003e\n\u003cp\u003eIn this course, you’ll begin by learning the design life cycle. This is the process by which we investigate user needs, brainstorm potential designs, create prototypes, and evaluate those prototypes. This life cycle provides the structure for the third and fourth courses in this professional certificate. \u003c/p\u003e\n\u003cp\u003eA key part of the design life cycle, however, is human subjects research. In interface design, this involves asking users for information about what they do and what they need, and then asking them for feedback on the prototypes that you develop. In HCI more broadly, this may involve testing different ideas with users to see what facilitates the best user experience. Whenever we interact with users, though, we need to keep in mind users’ rights to privacy and transparency, and so we begin this course with a discussion of ethics in HCI. This is grounded in the university Institutional Review Board process, but also investigates the role of ethics in HCI in industry as well. \u003c/p\u003e\n\u003cp\u003eFrom there, you’ll move on to needfinding and requirements gathering. It is always tempting to jump straight into designing an interface based on our intuitive understanding of a task or need, but successful interface design always starts with an understanding of the users: who are they, what they do, and what they need. This involves both interacting directly with them via surveys and interviews, as well as observing them at a distance or even attempting the tasks ourselves. This concludes with an understanding of the requirements of any interface we create. \u003c/p\u003e\n\u003cp\u003eFrom there, you’ll move on to brainstorming design alternatives. Again, it is often tempting to jump straight to the design we have in mind, but successful interface design starts with the results of needfinding and attempts a more grounded investigation of possible solutions. Through this lesson, you’ll learn techniques for managing effective brainstorming sessions and approaches to exploring the ideas that are created including artifacts like user personas, interaction timelines, and storyboards. \u003c/p\u003e\n\u003cp\u003eFinally, you’ll conclude by learning about prototyping. Implementing an interface is a complicated process, and there is a risk that we may invest lots of time into an interface that is doomed to fail because we do not get user feedback on the idea. The goal of prototyping is to get an idea in front of users as quickly as possible to validate and improve it before we move on to the high pressures of implementation. \u003c/p\u003e\n\u003cp\u003eBy the end of this course, you’ll have an understanding of the design life cycle and its first three major stages: needfinding, brainstorming, and prototyping. You’ll also understand the ethical implications of HCI research and how to safeguard users’ rights.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"357:T55b,\u003cul\u003e\n\u003cli\u003eThe structure of the design life cycle: needfinding, brainstorming, prototyping, and evaluation.\u003c/li\u003e\n\u003cli\u003eThe value of research ethics and the importance of emphasizing the user’s rights.\u003c/li\u003e\n\u003cli\u003eThe role of Institutional Review Boards in governing university research.\u003c/li\u003e\n\u003cli\u003eThe importance of ethics in industry and the mechanisms for ensuring they are maintained.\u003c/li\u003e\n\u003cli\u003eThe importance of needfinding in the design life cycle.\u003c/li\u003e\n\u003cli\u003eMechanisms for active needfinding, including surveys, interviews, and focus groups.\u003c/li\u003e\n\u003cli\u003eApproaches to personal needfinding, including participant observation and apprenticeship.\u003c/li\u003e\n\u003cli\u003eWays to observe organic interaction, such as naturalistic observation or investigation of hacks and workarounds.\u003c/li\u003e\n\u003cli\u003eThe data inventory, a structure for ensuring you understand your user and their problems.\u003c/li\u003e\n\u003cli\u003eApproaches to brainstorming design ideas, both individually and in groups.\u003c/li\u003e\n\u003cli\u003eMethods for further exploring design ideas, such as user personas and storyboards.\u003c/li\u003e\n\u003cli\u003eThe spectrum of prototyping, from low-fidelity to high-fidelity.\u003c/li\u003e\n\u003cli\u003eThe importance of low-fidelity prototypes in getting early feedback.\u003c/li\u003e\n\u003cli\u003eApproaches to low-fidelity prototyping, such as paper prototypes and Wizard of Oz.\u003c/li\u003e\n\u003cli\u003eMulti-level prototyping, or prototyping at variouslevels of abstraction.\u003c/li\u003e\n\u003c/ul\u003e358:T9bc,"])</script><script>self.__next_f.push([1,"\u003cp\u003eThis course takes you through the last nine lessons of CS6750: Human-Computer Interaction as taught in the Georgia Tech Online Master of Science in Computer Science program. \u003c/p\u003e\n\u003cp\u003eIn this final course in the professional certificate, you’ll complete your understanding of the design life cycle, and learn about the modern relevance of human-computer interaction. \u003c/p\u003e\n\u003cp\u003eYou’ll begin by learning about evaluation. This is the critical final step of the design life cycle, where we put our prototypes in front of real users (or strong approximations thereof) to get feedback on their quality. You’ll learn about three methods for evaluation: first, qualitative evaluation lets you get direct feedback on the strengths and weaknesses of your interface from real users. Second, quantitative evaluation lets you make strong claims about the effectiveness of your interface or the validity of your theories of interaction. Third, heuristic evaluation lets you inject evaluation much more completely into the design process, persistently putting yourself into the mindset of a user to investigate an interface. \u003c/p\u003e\n\u003cp\u003eThen, you’ll learn how human-computer interaction relates to a modern trend in software development, Agile design. HCI and Agile development have a deep symbiosis in the way they each value rapid feedback. Moreover, modern technologies have allowed high-fidelity prototypes to be developed with the relative ease of low-fidelity prototypes in the past, allowing even better feedback and evaluation to come in throughout the design process. \u003c/p\u003e\n\u003cp\u003eAfter wrapping up your understanding of the design life cycle and its iterative nature, you’ll turn your attention to a deeper dive into the modern state of human-computer interaction. You’ll have the chance to explore cutting-edge research in HCI, from technologies like extended reality to domains like cybersecurity to ideas like gesture-based interaction. HCI is a dynamic and evolving field, and any education it would not be complete without a chance to look at what’s happening today. \u003c/p\u003e\n\u003cp\u003eFinally, you’ll conclude by looking at how far you’ve come and what you could do next. From other MOOCs to graduate degrees in the field, there are enormous possibilities for further studies in HCI. \u003c/p\u003e\n\u003cp\u003eBy the end of this course, you’ll have an understanding of the importance of evaluation in the design life cycle, as well as an understanding of where HCI sits in modern development and research.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"359:T66e,\u003cp\u003eIn order to be competitive in the computer science field, it’s imperative to understand the basic building blocks of a modern computer and how they directly impact the speed and efficiency of a program. Whether you work with embedded systems, mobile computer-based systems, or cloud systems, performance and energy efficiency are key drivers of usability and competitiveness of computerized products.\u003c/p\u003e\n\u003cp\u003eIn this course, you will learn how to design modern multicore-based computers, and how the design choices you make affect performance and energy consumption. You will explore design principles governing modern microprocessors, such as pipelining and cache memories, as well as methods for determining the impact of your design on execution time and energy efficiency.\u003c/p\u003e\n\u003cp\u003eThese skills can make a difference for practicing engineers for the purpose of building highly competitive products. Take, for instance, a smartphone with limited battery capacity. By adding value to end users through new or improved functionality, this can lead to significantly shorter operation time between battery charges, thus utilizing the already limited resources of a smartphone far more efficiently.\u003c/p\u003e\n\u003cp\u003eWith this skillset, you can become an expert in computer system performance and energy efficiency - knowledge that is in high demand when designing computerized embedded products. With trends towards IoT (Internet of Things), autonomous systems and mobile computers, such a skillset will be critical in a career in systems engineering.\u003c/p\u003e\n\u003cp\u003eThis course is derived from a Chalmers senior undergraduate course in computer system design.\u003c/p\u003e35a:T764,\u003cp\u003eIl mondo moderno è sempre più dipendente dall’Informatica e conoscerne i fondamenti e le relative applicazioni risulta essenziale per comprendere il funzionamento degli attuali Sistemi di Elaborazione delle Informazioni, oramai diffusi nei contesti più disparati ed imprescindibili per molte delle attività della nostra vita quotidiana. Il corso di Fondamenti di Informatica "])</script><script>self.__next_f.push([1,"si propone di fornire ai discenti le nozioni preliminari alla base dell’informatica, ed in particolare quelle relative al trattamento delle informazioni mediante procedure “automatizzabili”. In tale ottica, il corso avrà per oggetto lo studio della rappresentazione delle informazioni, dell'architettura del calcolatore e degli algoritmi e programmi. Saranno nel contempo fornite tutte le competenze teoriche, metodologiche e pratiche fondamentali per la realizzazione di programmi di limitata complessità attraverso linguaggi di programmazione ad alto livello, con particolare riferimento alla programmazione strutturata ed al linguaggio C/C++ . \u003c/p\u003e\n\u003cp\u003eThe modern world is ever more dependent on computer science and information technology advances, and it has become essential to know the related basics and relevant applications so we can understand how the information systems, which we encounter in multiple and unexpected apsects of our everyday life, work. The Fundamentals of Informatics course aims to provide learners with the basic notions underlying computer science, especially the way information is processed using “automatable” procedures. The focus of the course, therefore, is on information representation, computer architecture, algorithms and programming. Learners will also acquire the necessary theory, methodologies and practice to design their own fairly simple programmes using high-level programming language, especially structured programming and C/C++ languages.\u003c/p\u003e35b:T6ac,\u003cp\u003eIs my program correct? Will it give the right output for all possible permitted inputs? Computers are now essential in everyday life. Incorrect programs lead to frustration in the best case and disaster in the worst. Thus, knowing how to construct correct programs is a skill that all who program computers must strive to master.\u003c/p\u003e\n\u003cp\u003eIn this computer science course, we will present \"goal oriented programming\" the way Edsger Dijkstra, one of the most influential computer scientists, intended. You will learn how to derive p"])</script><script>self.__next_f.push([1,"rograms hand-in-hand with their proofs of correctness. The course presents a methodology that illustrates goal-oriented programming, starting with the formalization of what is to be computed, and then growing the program hand-in-hand with its proof of correctness. The methodology demonstrates that, for a broad class of matrix operations, the development, implementation, and establishment of correctness of a program can be made systematic.\u003c/p\u003e\n\u003cp\u003eSince this technique focuses on program specifications, it often leads to clearer, correct programs in less time. The approach rapidly yields a family of algorithms from which you can then pick the algorithm that has desirable properties, such as attaining better performance on a given architecture.\u003c/p\u003e\n\u003cp\u003eThe audience of this MOOC extends beyond students and scholars interested in the domains of linear algebra algorithms and scientific computing. This course shows how to make the formal derivation of algorithms practical and will leave you pondering how our results might extend to other domains.\u003c/p\u003e\n\u003cp\u003eAs a result of support from MathWorks, learners will be granted access to MATLAB for the duration of the course.\u003c/p\u003e35c:T47f,\u003cp\u003eGoogle AI for Anyone teaches you about what Artificial Intelligence is. You’ll cut through the hype and learn about AI and Machine Learning.\u003c/p\u003e\n\u003cp\u003eAs its name suggests, this course is for anybody -- you don’t need a computer science, mathematics or AI background to understand it. No programming skills or prior knowledge are needed.\u003c/p\u003e\n\u003cp\u003eWe’ll take you through, from first principles what the fuss is all about, and you’ll get hands-on in playing with data to teach a computer how to recognize images, sounds and more.\u003c/p\u003e\n\u003cp\u003eAs you explore how AI is used in the real world (recommender systems, computer vision, self-driving etc.) you will also begin to build an understanding of Neural networks and the types of machine learning including supervised, unsupervised, reinforcement etc. You will also see (and experience) what programming AI looks "])</script><script>self.__next_f.push([1,"like and how it is applied.\u003c/p\u003e\n\u003cp\u003eFrom here you will be able to continue your journey through the emerging fields of AI and ML and related technologies. In so doing, you will formulate a basis to understand and discuss AI and ML related matters in your personal and professional life.\u003c/p\u003e35d:T5ed,\u003cp\u003eBasic concepts of computer programming are introduced, starting with the notion of an algorithm. Emphasis is on developing the ability to write programs to solve practical computational problems.\u003c/p\u003e\n\u003cp\u003eTopics include:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eAlgorithms\u003c/li\u003e\n\u003cli\u003eElements of C/C++ programming languages\u003c/li\u003e\n\u003cli\u003eBasic data types\u003c/li\u003e\n\u003cli\u003eSequential and conditional execution\u003c/li\u003e\n\u003cli\u003eIterative solutions\u003c/li\u003e\n\u003cli\u003eArrays, matrices and their applications\u003c/li\u003e\n\u003cli\u003eFunctions\u003c/li\u003e\n\u003cli\u003eSorting and searching\u003c/li\u003e\n\u003cli\u003eElements of string processing\u003c/li\u003e\n\u003cli\u003eIntroduction to pointers\u003c/li\u003e\n\u003cli\u003eBasics of Software Engineering\u003c/li\u003e\n\u003cli\u003eStructures\u003c/li\u003e\n\u003cli\u003eFile Processing\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eLearners will read and understand many sample programs, and will have to write several on their own. This course deals with basic programming, and sets the foundation for solid programming practices for beginners.\u003c/p\u003e\n\u003cp\u003eThis course is part of the \u003ca href=\"https://www.edx.org/xseries/fundamentals-computer-science\"\u003eFundamentals of Computer Science XSeries Program\u003c/a\u003e:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/object-oriented-programming-iitbombayx-cs101-2x\"\u003eObject-Oriented Programming\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/foundations-data-structures-iitbombayx-cs213-1x#!\"\u003eFoundations of Data Structures\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/implementation-data-structures-iitbombayx-cs213-2x\"\u003eImplementation of Data Structures\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/algorithms-2\"\u003eAlgorithms\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e35e:Ta05,"])</script><script>self.__next_f.push([1,"\u003cp\u003eThis course concentrates on recognizing and solving convex optimization problems that arise in applications. The syllabus includes: convex sets, functions, and optimization problems; basics of convex analysis; least-squares, linear and quadratic programs, semidefinite programming, minimax, extremal volume, and other problems; optimality conditions, duality theory, theorems of alternative, and applications; interior-point methods; applications to signal processing, statistics and machine learning, control and mechanical engineering, digital and analog circuit design, and finance.\u003c/p\u003e\n\u003cp\u003eThis course should benefit anyone who uses or will use scientific computing or optimization in engineering or related work (e.g., machine learning, finance). More specifically, people from the following fields: Electrical Engineering (especially areas like signal and image processing, communications, control, EDA \u0026amp; CAD); Aero \u0026amp; Astro (control, navigation, design), Mechanical \u0026amp; Civil Engineering (especially robotics, control, structural analysis, optimization, design); Computer Science (especially machine learning, robotics, computer graphics, algorithms \u0026amp; complexity, computational geometry); Operations Research; Scientific Computing and Computational Mathematics. The course may be useful to students and researchers in several other fields as well: Mathematics, Statistics, Finance, Economics.\u003c/p\u003e\n\u003cp\u003eAdditional Instructors / Contributors\u003c/p\u003e\n\u003cp\u003eNeal Parikh\u003c/p\u003e\n\u003cp\u003eNeal Parikh is a 5th year Ph.D. Candidate in Computer Science at Stanford University. He has previously taught Convex Optimization (EE 364A) at Stanford University and holds a B.A.S., summa cum laude, in Mathematics and Computer Science from the University of Pennsylvania and an M.S. in Computer Science from Stanford University.\u003c/p\u003e\n\u003cp\u003eErnest Ryu\u003c/p\u003e\n\u003cp\u003eErnest Ryu is a PhD candidate in Computational and Mathematical Engineering at Stanford University. He has served as a TA for EE364a at Stanford. His research interested include stochastic optimization, convex analysis, and scientific computing.\u003c/p\u003e\n\u003cp\u003eMadeleine Udell\u003c/p\u003e\n\u003cp\u003eMadeleine Udell is a PhD candidate in Computational and Mathematical Engineering at Stanford University. She has served as a TA and as an instructor for EE364a at Stanford. Her research applies convex optimization techniques to a variety of non-convex applications, including sigmoidal programming, biconvex optimization, and structured reinforcement learning problems, with applications to political science, biology, and operations research.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"35f:T5e1,\u003cp\u003eAlgorithms power the biggest web companies and the most promising startups. Interviews at tech companies start with questions that probe for good algorithm thinking.\u003c/p\u003e\n\u003cp\u003eIn this computer science course, you will learn how to think about algorithms and create them using sorting techniques such as quick sort and merge sort, and searching algorithms, median finding, and order statistics.\u003c/p\u003e\n\u003cp\u003eThe course progresses with Numerical, String, and Geometric algorithms like Polynomial Multiplication, Matrix Operations, GCD, Pattern Matching, Subsequences, Sweep, and Convex Hull. It concludes with graph algorithms like shortest path and spanning tree.\u003c/p\u003e\n\u003cp\u003eTopics covered:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eSorting and Searching\u003c/li\u003e\n\u003cli\u003eNumerical Algorithms\u003c/li\u003e\n\u003cli\u003eString Algorithms\u003c/li\u003e\n\u003cli\u003eGeometric Algorithms\u003c/li\u003e\n\u003cli\u003eGraph Algorithms\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThis course is part of the \u003ca href=\"https://www.edx.org/xseries/fundamentals-computer-science\"\u003eFundamentals of Computer Science XSeries Program\u003c/a\u003e:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/programming-basics-iitbombayx-cs101-1x\"\u003eProgramming Basics\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/object-oriented-programming-iitbombayx-cs101-2x\"\u003eObject-Oriented Programming\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/foundations-data-structures-iitbombayx-cs213-1x#!\"\u003eFoundations of Data Structures\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/implementation-data-structures-iitbombayx-cs213-2x\"\u003eImplementation of Data Structures\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e360:T4f8,\u003cp\u003eEverywhere you look, people are talking about AI. This course will help you better understand AI and how you can more effectively interact with it.\u003c/p\u003e\n\u003cp\u003eAI is a field of computer science that enables computers to simulate human intelligence. AI systems function by ingesting very large amounts of data. Similarly to how a human would, it “learns” from this data, and then uses that knowledge to predict future data and solve complex problems that, up until recently, could only be solved by humans.\u003c/p\u003e\n\u003cp\u003eThe term "])</script><script>self.__next_f.push([1,"“prompt” refers to the text that the user gives to the AI algorithm to tell it what to do. If you’ve ever tried to use ChatGPT or another AI model, you’ve already generated an AI prompt, but in order to generate the best output from a generative AI model, you must understand the opportunities and limitations of these models. This knowledge will help you phrase your prompt in a way that best allows the model to meet your needs.\u003c/p\u003e\n\u003cp\u003eThis course focuses on the methodology of: \u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eCrafting AI prompts to avoid AI hallucinations\u003c/li\u003e\n\u003cli\u003eUsing examples and data in your prompts to help AI algorithms provide the most useful outputs for your needs \u003c/li\u003e\n\u003cli\u003eUtilizing key words to improve responses from AI algorithms\u003c/li\u003e\n\u003c/ul\u003e361:T6e3,\u003cp\u003eThis Statistics for Data Science course is designed to introduce you to the basic principles of statistical methods and procedures used for data analysis. After completing this course you will have practical knowledge of crucial topics in statistics including - data gathering, summarizing data using descriptive statistics, displaying and visualizing data, examining relationships between variables, probability distributions, expected values, hypothesis testing, introduction to ANOVA (analysis of variance), regression and correlation analysis. You will take a hands-on approach to statistical analysis using Python and Jupyter Notebooks – the tools of choice for Data Scientists and Data Analysts.\u003c/p\u003e\n\u003cp\u003eAt the end of the course, you will complete a project to apply various concepts in the course to a Data Science problem involving a real-life inspired scenario and demonstrate an understanding of the foundational statistical thinking and reasoning. The focus is on developing a clear understanding of the different approaches for different data types, developing an intuitive understanding, making appropriate assessments of the proposed methods, using Python to analyze our data, and interpreting the output accurately. This course is suitable for a variety of professionals an"])</script><script>self.__next_f.push([1,"d students intending to start their journey in data and statistics-driven roles such as Data Scientists, Data Analysts, Business Analysts, Statisticians, and Researchers. It does not require any computer science or statistics background. We strongly recommend taking the Python for Data Science course before starting this course to get familiar with the Python programming language, Jupyter notebooks, and libraries. An optional refresher on Python is also provided.\u003c/p\u003e362:T9da,"])</script><script>self.__next_f.push([1,"\u003cp\u003e6.341x is designed to provide both an in-depth and an intuitive understanding of the theory behind modern discrete-time signal processing systems and applications. The course begins with a review and extension of the basics of signal processing including a discussion of group delay and minimum-phase systems, and the use of discrete-time (DT) systems for processing of continuous-time (CT) signals. The course develops flow-graph and block diagram structures including lattice filters for implementing DT systems, and techniques for the design of DT filters. Parametric signal modeling and the efficient implementation of DT multirate and sampling rate conversion systems are discussed and developed. An in-depth development of the DFT and its computation as well as its use for spectral analysis and for filtering is presented. This component of the course includes a careful and insightful development of the relationship between the time-dependent Fourier transform and the use of filter banks for both spectral analysis and signal coding.\u003c/p\u003e\n\u003cp\u003e6.341x is organized around eleven units each typically consisting of a set of two to four topics. The source material for learning each topic includes suggested reading in the course text, clarifying notes, other related reading, and video excerpts and will include an interactive on-line discussion forum. The course text is the widely used text by Oppenheim and Schafer (third edition). The video segments are adapted from live video recordings of the MIT residential course. \u003c/p\u003e\n\u003cp\u003eEach topic includes a set of automatically-graded exercises for self-assessment and to help in digesting and understanding the basics of the topic, and in some cases to preview topics. A typical unit in the course concludes with a set of more extensive problems to help in integrating the topics and developing a deeper understanding. Automatic grading of your answers to these problems as well as solutions will be provided.\u003c/p\u003e\n\u003cp\u003e6.341x and this freely-available version were developed through the support and encouragement of the MIT Department of Electrical Engineering and Computer Science, the MIT Office of Digital Learning, and the MIT Research Laboratory of Electronics.\u003c/p\u003e\n\u003cp\u003eThis course can be cited as: Alan V. Oppenheim and Thomas A. Baran, 6.341x Discrete-Time Signal Processing, on edX, Summer 2016. \u003ca href=\"https://www.edx.org/course/discrete-time-signal-processing-mitx-6-341x-1\"\u003ehttps://www.edx.org/course/discrete-time-signal-processing-mitx-6-341x-1\u003c/a\u003e\u003c/p\u003e"])</script><script>self.__next_f.push([1,"363:T6c8,\u003cp\u003eData structures play a central role in computer science and are the cornerstones of efficient algorithms. Knowledge in this area has been at the kernel of related curriculums. This course aims at exploring the principles and methods in the design and implementation of various data structures and providing students with main tools and skills for algorithm design and performance analysis. Topics covered by this course range from fundamental data structures to recent research results. \"Data Structures and Algorithm Design Part I\" is an introductory course focusing on basic data structures, including vectors, lists, stacks, queues, binary trees, and graphs. They are important in programming practice, as well as fundamental to our advanced course: \"Part II.\"\u003c/p\u003e\n\u003cp\u003eData structures are a key component of computer science and a necessary foundation for building efficient algorithms. The knowledge it covers has always been at the core of the curriculum system of related majors. This course aims to focus on the design and implementation of various data structures and reveal the regular principles and methods and techniques; at the same time, it aims to enable students to understand and master the main routines and techniques for algorithm design and performance analysis. The topics taught range from basic data structures to recent research results. This semester's Data Structure (Part 1) is an introductory course on data structures, focusing on basic data structures such as vectors, lists, stacks, queues, binary trees, graphs, etc. Structure (Part 2)\" provides the basis. For more detailed introduction, please see: http://dsa.cs.tsinghua.edu.cn/~deng/ds/mooc/, or check the FAQ column after joining this course.\u003c/p\u003e364:Tc08,"])</script><script>self.__next_f.push([1,"\u003cp\u003eIn recent years, flying robots such as miniature helicopters or quadrotors have received a large gain in popularity. Potential applications range from aerial filming over remote visual inspection of industrial sites to automatic 3D reconstruction of buildings. Navigating a quadrotor manually requires a skilled pilot and constant concentration. Therefore, there is a strong scientific interest to develop solutions that enable quadrotors to fly autonomously and without constant human supervision. This is a challenging research problem because the payload of a quadrotor is uttermost constrained and so both the quality of the onboard sensors and the available computing power is strongly limited. \u003c/p\u003e\n\u003cp\u003eIn this course, we will introduce the basic concepts for autonomous navigation for quadrotors. The following topics will be covered:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e3D geometry,\u003c/li\u003e\n\u003cli\u003eprobabilistic state estimation,\u003c/li\u003e\n\u003cli\u003evisual odometry, SLAM, 3D mapping,\u003c/li\u003e\n\u003cli\u003elinear control.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eIn particular, you will learn how to infer the position of the quadrotor from its sensor readings and how to navigate it along a trajectory.\u003c/p\u003e\n\u003cp\u003eThe course consists of a series of weekly lecture videos that we be interleaved by interactive quizzes and hands-on programming tasks. For the flight experiments, we provide a browser-based quadrotor simulator which requires the students to write small code snippets in Python.\u003c/p\u003e\n\u003cp\u003eThis course is intended for undergraduate and graduate students in computer science, electrical engineering or mechanical engineering. This course has been offered by TUM for the first time in summer term 2014 on EdX with more than 20.000 registered students of which 1400 passed examination. The MOOC is based on the previous TUM lecture “Visual Navigation for Flying Robots” which received the TUM TeachInf best lecture award in 2012 and 2013.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFAQ\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDo I need to buy a textbook?\u003c/p\u003e\n\u003cp\u003eNo, all required materials will be provided within the courseware. However, if you are interested, we recommend the following additional materials:\u003c/p\u003e\n\u003col\u003e\n\u003cli\u003eThis course is based on the TUM lecture Visual Navigation for Flying Robots. The course website contains lecture videos (from last year), additional exercises and the full syllabus: \u003ca href=\"http://vision.in.tum.de/teaching/ss2013/visnav2013\"\u003ehttp://vision.in.tum.de/teaching/ss2013/visnav2013\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"http://www.probabilistic-robotics.org/\"\u003eProbabilistic Robotics\u003c/a\u003e. Sebastian Thrun, Wolfram Burgard and Dieter Fox. MIT Press, 2005.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"http://szeliski.org/Book/\"\u003eComputer Vision: Algorithms and Applications\u003c/a\u003e. Richard Szeliski. Springer, 2010.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eDo I need to build/own a quadrotor?\u003c/p\u003e\n\u003cp\u003eNo, we provide a web-based quadrotor simulator that will allow you to test your solutions in simulation. However, we took special care that the code you will be writing will be compatible with a real Parrot Ardrone quadrotor. So if you happen to have a Parrot Ardrone quadrotor, we encourage you to try out your solutions for real.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"365:T45b,\u003cp\u003eThis quantum computing course explores the basic design principles of today's quantum computer systems. In this course, students will learn to work with the IBM Qiskit software tools to write simple programs in Python and execute them on cloud-accessible quantum hardware. Topics covered in this course include:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eIntroduction to systems research in quantum computing\u003c/li\u003e\n\u003cli\u003eFundamental rules in quantum computing, Bloch Sphere, Feynman Path Sum\u003c/li\u003e\n\u003cli\u003eSequential and parallel execution of quantum gates, EPR pair, no-cloning theorem, quantum teleportation\u003c/li\u003e\n\u003cli\u003eMedium-size algorithms for NISQ (near-term intermediate scale quantum) computers\u003c/li\u003e\n\u003cli\u003eQuantum processor microarchitecture: classical and quantum control\u003c/li\u003e\n\u003cli\u003eQuantum program compilation and qubit memory management\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eKeywords: quantum computing, computer science, linear algebra, compiler, circuit optimization, python, qiskit, quantum algorithms, quantum technology, superposition, entanglement, qubit technology, superconducting qubit, transmon qubit, ion-trap qubit, photonic qubit, real quantum computers\u003c/p\u003e366:T401,\u003cp\u003eLaTeX, a document preparation system, is widely used for publishing in many scientific fields like mathematics, statistics, computer science, engineering, chemistry, physics, economics, linguistics, etc.. It is a powerful and open-source system that provides numerous facilities for automating typesetting of the document: i.e. structuring page layout, listing and auto-numbering of sections, tables, figures, generating a table of contents, managing cross-referencing, citing, and indexing. \u003c/p\u003e\n\u003cp\u003eUnlike other WYSIWYG editors, the content is written in plain text along with appropriate commands, thus, allowing the user to concentrate on the content rather than the aesthetics (the way it looks). The TeX typesetting program which LaTeX uses, was designed such that anyone can create good quality material with less efforts. \u003c/p\u003e\n\u003cp\u003eThis course introduces the basic concepts of LaTeX. Participants taking thi"])</script><script>self.__next_f.push([1,"s course will be able to create and design documents in LaTeX and presentations in Beamer with confidence.\u003c/p\u003e367:Ta51,"])</script><script>self.__next_f.push([1,"\u003cp\u003eThe increased demand by consumers and businesses for more utility, connectivity and smarter and more efficient electronic technology not only creates a need for more embedded systems but also for engineers in the embedded systems field.\u003c/p\u003e\n\u003cp\u003eIn this lab-based computer science course, explore the complexities of embedded systems and learn how to develop your own \u003cstrong\u003ereal-time operating system\u003c/strong\u003e (RTOS) by building a personal fitness device with \u003cstrong\u003eBluetooth connectivity\u003c/strong\u003e (BLE). An \u003cstrong\u003eoperating system\u003c/strong\u003e (OS) is a software system that computers use to manage the resources of a computer. The OS decides which tasks are performed when and decides how resources are utilized. Simple embedded systems, which are a combination of electrical, mechanical, chemical, and computer components designed to perform a dedicated function, originally did not need an OS. However, as embedded systems have evolved, so have their complexities. To manage this, an RTOS \u003cstrong\u003eis now required\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eEmbedded systems are often deployed in safety-critical situations such as automotive, military, industrial, and medical applications. In applications such as communications and consumer electronics, response time and processing speed are important. A real-time system not only needs to arrive at the correct answer, but must also get the correct answer at the correct time. A RTOS manages a computer's resources so that tasks are performed in a timely mannner.\u003c/p\u003e\n\u003cp\u003eIn this computer science course, students will learn the design fundamentals of an \u003cstrong\u003eRTOS\u003c/strong\u003e from the bottom up and use these fundamentals to build practical real-time applications. We will provide a board support package (BSP), so students will be able to focus on the RTOS and Bluetooth network without needing prior experience in circuits and I/O device driver software. This is a \u003cstrong\u003ehands-on project-based lab course\u003c/strong\u003e , where you will incrementally build a personal fitness device with Bluetooth connectivity.\u003c/p\u003e\n\u003cp\u003eThis course is intended for students and professional engineers wishing to improve their skills in the fields of embedded systems, product development, computer architecture, operating systems, and Bluetooth networks.\u003c/p\u003e\n\u003cp\u003eTo complete this course, you will need to \u003cstrong\u003epurchase a lab kit\u003c/strong\u003e including a microcontroller board, an I/O board, and a Bluetooth module. Instructions about purchasing the kit and installing required software are at \u003ca href=\"http://edx-org-utaustinx.s3.amazonaws.com/UT601x/RTOS.html\"\u003ehttp://edx-org-utaustinx.s3.amazonaws.com/UT601x/RTOS.html \u003c/a\u003e.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"368:T40a,\u003cp\u003eIn this Computer Science course, you will learn about implementation of all major abstract data structures using object-oriented programming paradigm of C++.\u003c/p\u003e\n\u003cp\u003eThis course builds on the basic concepts developed in ‘Foundations of Data Structures’ course.\u003c/p\u003e\n\u003cp\u003eTopics covered:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eReview of OO programming, STL of C++\u003c/li\u003e\n\u003cli\u003eStacks\u003c/li\u003e\n\u003cli\u003eQueues\u003c/li\u003e\n\u003cli\u003eLists\u003c/li\u003e\n\u003cli\u003eTrees\u003c/li\u003e\n\u003cli\u003eGraphs\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThis course is part of the \u003ca href=\"https://www.edx.org/xseries/fundamentals-computer-science\"\u003eFundamentals of Computer Science XSeries Program\u003c/a\u003e:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/programming-basics-iitbombayx-cs101-1x\"\u003eProgramming Basics\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/object-oriented-programming-iitbombayx-cs101-2x\"\u003eObject-Oriented Programming\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/foundations-data-structures-iitbombayx-cs213-1x#!\"\u003eFoundations of Data Structures\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/algorithms-2\"\u003eAlgorithms\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e369:T45b,\u003cp\u003eThis quantum computing course explores the basic design principles of today's quantum computer systems. In this course, students will learn to work with the IBM Qiskit software tools to write simple programs in Python and execute them on cloud-accessible quantum hardware. Topics covered in this course include:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eIntroduction to systems research in quantum computing\u003c/li\u003e\n\u003cli\u003eFundamental rules in quantum computing, Bloch Sphere, Feynman Path Sum\u003c/li\u003e\n\u003cli\u003eSequential and parallel execution of quantum gates, EPR pair, no-cloning theorem, quantum teleportation\u003c/li\u003e\n\u003cli\u003eMedium-size algorithms for NISQ (near-term intermediate scale quantum) computers\u003c/li\u003e\n\u003cli\u003eQuantum processor microarchitecture: classical and quantum control\u003c/li\u003e\n\u003cli\u003eQuantum program compilation and qubit memory management\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eKeywords: quantum computing, computer science, linear algebra, compiler, circuit optimization, python, qiskit, quantum algorithms, quantum technology, superposition, entangleme"])</script><script>self.__next_f.push([1,"nt, qubit technology, superconducting qubit, transmon qubit, ion-trap qubit, photonic qubit, real quantum computers\u003c/p\u003e36a:T478,\u003cp\u003eWe live in the information age, and we are inundated with information on a daily basis. With so much information coming at us so fast, how do we know what’s true? How do we know which information is real? How can we fact-check what we read and see?\u003c/p\u003e\n\u003cp\u003eIn this class, you will explore the answers to these questions by learning information literacy. You will learn how to evaluate the information you see on the Internet as well as academic information. You will also learn how to access credible sources of information and share that information with others.\u003c/p\u003e\n\u003cp\u003eIn later modules, you will learn about different types of sources, how to develop an academic research question, and how to find scholarly sources on that topic. The course concludes with modules about formally presenting your research, citing it properly, and ensuring academic integrity by avoiding plagiarism.\u003c/p\u003e\n\u003cp\u003eThis course can be used to fulfill the Information Literacy requirement at Thomas Edison State University in the Bachelor of Arts in Computer Science Degree. It will not satisfy the Information Literacy Requirements in any other degrees at TESU.\u003c/p\u003e36b:T45b,\u003cp\u003eThis quantum computing course explores the basic design principles of today's quantum computer systems. In this course, students will learn to work with the IBM Qiskit software tools to write simple programs in Python and execute them on cloud-accessible quantum hardware. Topics covered in this course include:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eIntroduction to systems research in quantum computing\u003c/li\u003e\n\u003cli\u003eFundamental rules in quantum computing, Bloch Sphere, Feynman Path Sum\u003c/li\u003e\n\u003cli\u003eSequential and parallel execution of quantum gates, EPR pair, no-cloning theorem, quantum teleportation\u003c/li\u003e\n\u003cli\u003eMedium-size algorithms for NISQ (near-term intermediate scale quantum) computers\u003c/li\u003e\n\u003cli\u003eQuantum processor microarchitecture: classical and quantum control\u003c/li\u003e\n\u003cli\u003eQuantum program c"])</script><script>self.__next_f.push([1,"ompilation and qubit memory management\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eKeywords: quantum computing, computer science, linear algebra, compiler, circuit optimization, python, qiskit, quantum algorithms, quantum technology, superposition, entanglement, qubit technology, superconducting qubit, transmon qubit, ion-trap qubit, photonic qubit, real quantum computers\u003c/p\u003e36c:T5cc,\u003cp\u003eSee your favorite games like never before! \u003c/p\u003e\n\u003cp\u003eEver wondered why farming for a mighty sword in a fantasy game feels entertaining and fun while filling out reporting documents – a seemingly similar repetitive activity – is incredibly boring? If so, you are not alone! \u003c/p\u003e\n\u003cp\u003eThe vast field of Gamification applies techniques and patterns from fundamental mechanics of game design to non-game contexts in order to make business tasks more fun for a user. This can lead to increased efficiency and accuracy and even facilitate better health by reducing exhaustion. \u003c/p\u003e\n\u003cp\u003eHowever, there is one particular requirement that often becomes a hurdle for Gamification efforts: meeting accessibility requirements. \u003c/p\u003e\n\u003cp\u003eIn this computer science course, we will investigate this use case closer and derive a new set of patterns that are representation-agnostic. You will learn the fundamentals of Gamification and accessibility, as well as lessons in game development and game design. We will take a look at popular digital games and draw patterns from their game design and game mechanics. \u003c/p\u003e\n\u003cp\u003eBy the end of this course, you will have gained a better grasp on the problem at hand and learn patterns and techniques to deploy gamification in a broader and more abstract scope. \u003c/p\u003e\n\u003cp\u003eBut be warned: you might see your favorite digital games like you never saw them before – as a wired, but well-tailored, combination of reward, development, discover and challenge.\u003c/p\u003e36d:T421,\u003cp\u003eThe world around us becomes immersed in technology, which is ultimately driven by programming and governed by its laws. We believe that high-level knowledge of means for programming ‒ past, pre"])</script><script>self.__next_f.push([1,"sent, and most importantly, future ‒ is of crucial interest to many. \u003c/p\u003e\n\u003cp\u003eThis course is designed to teach almost anyone about the essence of programming, about the diverse types of existing programming paradigms, about how programming has evolved over the years, and, significantly, about what it will entail in the future. \u003c/p\u003e\n\u003cp\u003eIn the main part of the course, we will present some visual, diagrammatic programming languages, and some of the more recent playful and intuitive approaches to programming. We hope to help people interested in technology, as well as computer science students, to better understand the various approaches to programming, which are becoming increasingly important in our lives. This course is meant to “Liberate Programming” - to provide more people with the understanding of what programming is and how it works.s\u003c/p\u003e36e:Tcaa,"])</script><script>self.__next_f.push([1,"\u003cp\u003e\u003cstrong\u003eThis course will soon be retired. Last day to enroll is 12/31/2022 at 00:00 UTC.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis is the 5th course in the intermediate, undergraduate-level offering that makes up the larger Cybersecurity Fundamentals MicroBachelors Program. We recommend taking them in order, unless you have a background in these areas already and feel comfortable skipping ahead.\u003c/p\u003e\n\u003col\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/information-security-introduction-to-information-security\"\u003eInformation Security - Introduction to Information Security\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/information-security-authentication-and-access-control\"\u003eInformation Security - Authentication and Access Control\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/information-security-advanced-topics\"\u003eInformation Security - Advanced Topics\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/network-security-introduction-to-network-security\"\u003eNetwork Security - Introduction to Network Security\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/network-security-protocols\"\u003eNetwork Security - Protocols\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/network-security-advanced-topics\"\u003eNetwork Security - Advanced Topics\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/penetration-testing-discovering-vulnerabilities\"\u003ePenetration Testing - Discovering Vulnerabilities\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/penetration-testing-exploitation\"\u003ePenetration Testing - Exploitation\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/penetration-testing-post-exploitation\"\u003ePenetration Testing - Post Exploitation\u003c/a\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThese topics build upon the learnings that are taught in the introductory-level Computer Science Fundamentals MicroBachelors program, offered by the same instructor.\u003c/p\u003e\n\u003cp\u003eThis is a self-paced course that provides a continuation of network security topics. Among the topics covered are cryptographic algorithms used in networking protocols, TLS/SSL, IPSec Layer 2 Security, and Wireless Security. The material is essential in later classes that will develop ethical hacking skills. Students are provided with a broad understanding of cryptography, from its classical applications dating from the Roman empire to modern cryptography, including the public key cryptography and hashing techniques today. Next, we take what we learned about cryptography and apply it as a tool against attackers. Specifically, we'll discuss IP Security, TLS/SSL, and its use in Virtual Private Networks. We follow up with coverage of Layer 2 security and vulnerabilities, such as MAC attacks, VLAN hopping attacks, DHCP attacks, ARP attacks, spoofing attacks, and attacks on other protocols. We'll also go over common countermeasures to these attacks. We conclude the course with an overview of how WiFi works, basic terminology and architecture, and how wireless networks are secured.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIndustry Certification Preparation\u003c/strong\u003e\u003cbr /\u003e\nThis program covers much of the material that is assessed on the \u003ca href=\"https://www.comptia.org/certifications/security\"\u003eCompTIA’s Security+ certification exam\u003c/a\u003e. Upon program completion, verified track learners will receive a 36% discount code for the CompTIA Security+ exam.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"36f:T818,"])</script><script>self.__next_f.push([1,"\u003col\u003e\n\u003cli\u003eDefine and apply a substitution cipher\u003c/li\u003e\n\u003cli\u003eDefine cryptanalysis\u003c/li\u003e\n\u003cli\u003eExplain at a high level the process by which a plaintext message is encrypted, transmitted, and decrypted.\u003c/li\u003e\n\u003cli\u003eDescribe at least two strategies for breaking an encryption scheme\u003c/li\u003e\n\u003cli\u003eIdentify the differences between public key encryption, symmetric key encryption, and hashing\u003c/li\u003e\n\u003cli\u003eList and summarize the characteristics of good ciphers\u003c/li\u003e\n\u003cli\u003eDescribe the vulnerabilities of stream ciphers\u003c/li\u003e\n\u003cli\u003eDefine AES and explain why it is recommended over 3DES\u003c/li\u003e\n\u003cli\u003eDefine cipher block chaining\u003c/li\u003e\n\u003cli\u003eList the steps in creating an RSA public/private key pair\u003c/li\u003e\n\u003cli\u003eExplain why RSA is secure\u003c/li\u003e\n\u003cli\u003eDefine message integrity and explain how it is ensured\u003c/li\u003e\n\u003cli\u003eDefine IPSec and list its services\u003c/li\u003e\n\u003cli\u003eDefine authentication header and ESP\u003c/li\u003e\n\u003cli\u003eExplain the primary goal of IKE and describe its sub-protocols\u003c/li\u003e\n\u003cli\u003eSummarize the five steps of IPSec Operation\u003c/li\u003e\n\u003cli\u003eSummarize the history of SSL\u003c/li\u003e\n\u003cli\u003eExplain how closure alerts can prevent a truncation attack\u003c/li\u003e\n\u003cli\u003eIdentify the protocols that make up the SSL architecture\u003c/li\u003e\n\u003cli\u003eDescribe how SSL/TLS provides protected channels\u003c/li\u003e\n\u003cli\u003eState the differences between IPSec and SSL VPN connections\u003c/li\u003e\n\u003cli\u003eExplain why it's important to consider Layer 2 security\u003c/li\u003e\n\u003cli\u003eDefine common Layer 2 attacks\u003c/li\u003e\n\u003cli\u003eIdentify tools used in Layer 2 attacks\u003c/li\u003e\n\u003cli\u003eDescribe countermeasures to Layer 2 attacks and security best practices to prevent attacks\u003c/li\u003e\n\u003cli\u003eExplain the differences between the 2.4GHz and 5GHz spectrums\u003c/li\u003e\n\u003cli\u003eProvide definitions of basic wireless terms\u003c/li\u003e\n\u003cli\u003eExplain how 802.11ac differs from earlier 802.11 standards\u003c/li\u003e\n\u003cli\u003eIdentify and define the types of 802.11 frames\u003c/li\u003e\n\u003cli\u003eList and define the states of 802.11 sessions\u003c/li\u003e\n\u003cli\u003eList the steps in establishing an 802.11 session\u003c/li\u003e\n\u003cli\u003eSummarize the existing wireless security protocols and state which protocols should not be used\u003c/li\u003e\n\u003cli\u003eSummarize WPA, WPA Enterprise, and generalized WiFi attacks\u003c/li\u003e\n\u003c/ol\u003e"])</script><script>self.__next_f.push([1,"370:T455,\u003cp\u003eReady to start your programming journey? Being a software engineer is much more than simply writing code--it requires a strong conceptual understanding of computer science. In this course, which was developed through a combination of academic and industry perspectives, learn not only how to code in Java but also how to break down problems and implement their solutions using some of the most fundamental computer science tools.\u003c/p\u003e\r\n\u003cp\u003eGet plenty of hands-on Java coding experience with methods, logic, loops, variables, parameters, returns, and recursion. And write your code using industry-standard tools and practices to help you build strong habits as you grow your development skill set.\u003c/p\u003e\r\n\u003cp\u003eWhether you are preparing for advanced university computer science courses, an entry-level software engineering position, or the Advanced Placement Computer Science A exam, get the tools you need to succeed in this practical, self-paced Java course.\u003c/p\u003e\r\n\u003cp\u003e\u003cstrong\u003e*Note:\u003c/strong\u003e *This course will retire at the end of October. Please enroll only if you are able to finish your coursework in time.\u003c/p\u003e371:T579,\u003cp\u003eDeveloped by Blockchain at Berkeley and faculty from UC Berkeley's premier Computer Science department, this course provides a wide overview of many of the topics relating to and building upon the foundation of Bitcoin and blockchain technology. \u003c/p\u003e\n\u003cp\u003eThe course covers many key topics in the blockchain space. First, we take a look at distributed systems and alternative consensus mechanisms, as well as cryptoeconomic and proof-of-stake. We then move on to the fundamental applications of bitcoin and blockchain technology, including exploring enterprise blockchain implementations (JP Morgan’s Quorum, Ripple, Tendermint, and HyperLedger), the challenges and solutions around scaling blockchain adoption, and the measures that the government is taking to regulate and control blockchain technology. We wrap up the course by also taking a look at the various blockchain ventures today and conclude with a blockch"])</script><script>self.__next_f.push([1,"ain-based future thought experiment. \u003c/p\u003e\n\u003cp\u003eThis course is open to anyone with any background. Whether you are planning your next career move as a blockchain developer, crypto trader, data analyst, researcher, or consultant, or are just looking for an introduction to Blockchain.This course will help you beginto develop the critical skills needed to future-proof your career. \u003c/p\u003e\n\u003cp\u003eThis is the second course in the Blockchain Fundamentals Professional Certificate program.\u003c/p\u003e372:T589,\u003cul\u003e\n\u003cli\u003eA formal definition of distributed consensus and foundational topics such as the CAP Theorem and the Byzantine Generals Problem.\u003c/li\u003e\n\u003cli\u003eThe alternative consensus mechanisms to Bitcoin’s Proof-of-work, including Proof-of-Stake, voting-based consensus algorithms, and federated consensus.\u003c/li\u003e\n\u003cli\u003eThe meaning and properties of cryptoeconomics as it relates to its two compositional fields: cryptography and economics, as well as the goals for cryptoeconomics with respect to distributed systems fundamentals\u003c/li\u003e\n\u003cli\u003eThe various enterprise-level blockchain implementations, such as JP Morgan’s Quorum, Ripple, Tendermint, and HyperLedger, including the industry use cases for blockchain, ICOs, and the increasing regulations surrounding blockchain.\u003c/li\u003e\n\u003cli\u003eThe challenges with scaling and obstacles to widespread blockchain adoption, as well as the possible solutions within vertical scaling (e.g. blocksize increases, Segregated Witness, and the Lightning Network) and horizontal scaling (e.g. sidechains, sharding).\u003c/li\u003e\n\u003cli\u003eThe measures that governments have taken to regulate and control blockchain technology e.g. Anti-Money Laundering (AML) and Know Your Customer (KYC) regulations, anonymity goals, and government techniques for deanonymization of entities on blockchain.\u003c/li\u003e\n\u003cli\u003eAn exploratory look into blockchain ventures today, such as venture capitalism, ICOs, and crowdfunding.\u003c/li\u003e\n\u003c/ul\u003e373:T5ba,\u003cp\u003eDeveloped by Blockchain at Berkeley and faculty from UC Berkeley's premier Computer Science department, this course presents Bitco"])</script><script>self.__next_f.push([1,"in and cryptocurrencies as the motivation for blockchain technologies, and provides a comprehensive and in-depth overview of the fundamental concepts of the crypto space with a particular emphasis on Bitcoin. \u003c/p\u003e\n\u003cp\u003eThe course covers basic properties of bitcoin, the mechanics behind it (e.g. including cryptographic hash functions, Bitcoin Script, privacy, and hash commitment schemes) and its roots in the Cypherpunk movement and Libertarian ideals. You'll learn about practical applications of Bitcoin such as wallets and mining, as well as how to destroy bitcoins, including network attacks and malicious mining strategies. We will also take a brief look at Ethereum and how blockchain can be used outside of cryptocurrencies. \u003c/p\u003e\n\u003cp\u003eThis course is open to anyone with any background. Whether you are planning your next career move as a blockchain developer, crypto trader, data analyst, researcher, or consultant, or are just looking for an introduction to the Bitcoin technology. This course will help you to begin developing the critical skills needed to future-proof your career. \u003c/p\u003e\n\u003cp\u003eThis course is part of the Blockchain Fundamentals Professional Certificateprogram. If you are planning to enroll in the entire series, we suggest starting with this course and then progressing on to CS198.2x Blockchain Technology.\u003c/p\u003e374:T41f,\u003cul\u003e\n\u003cli\u003eThe basic properties and intent of centralized/decentralized currency and an in-depth understanding of Bitcoin from the ground up, including - Identity, Transactions, Record Keeping, and Consensus.\u003c/li\u003e\n\u003cli\u003eThe roots of Bitcoin in the Cypherpunk movement and Libertarian ideals, and the revolutionary significance of Bitcoin as opposed to some of its early predecessors.\u003c/li\u003e\n\u003cli\u003eThe mechanics behind Bitcoin, such as the Bitcoin network, cryptography and cryptographic hash functions, Bitcoin Script, privacy, and hash commitment schemes.\u003c/li\u003e\n\u003cli\u003eReal-world aspects of Bitcoin, such as wallets, wallet mechanics, mining, transactions, and Bitcoin governance and the various ways one can interfac"])</script><script>self.__next_f.push([1,"e with the Bitcoin network.\u003c/li\u003e\n\u003cli\u003eHow to destroy Bitcoin, including various network attacks.\u003c/li\u003e\n\u003cli\u003eThe properties behind the second largest blockchain platform, Ethereum, including the Ethereum Virtual Machine and the idea of Turing completeness, the key protocol differences between Bitcoin and Ethereum, the use cases of Ethereum.\u003c/li\u003e\n\u003c/ul\u003e375:T4d4,\u003cp\u003eThere is no doubt that the quantum computer and the quantum internet have many profound applications, they may change the way we think about information, and they could completely change our daily life.The aim of this course is to help you get up to speed with current progress in the transition to a quantum information era. After an initial review of some of the basic concepts and operating principles of quantum computing and quantum information (e.g. the ket notation and quantum bits, the qubits), the course will feature an extensive discussion on some of the different ways qubits can be built. Then, we will discuss the four types of qubits that QuTech focuses on: topological qubits, spin qubits, superconducting qubits and NV center qubits.\u003c/p\u003e\n\u003cp\u003eThe course is a journey of discovery, so we encourage you to bring your own experiences, insights and thoughts via the forum!\u003c/p\u003e\n\u003cp\u003eThis course is authored by experts from the QuTech research center at Delft University of Technology. In the center, scientists and engineers work together to enhance research and development in quantum technology. QuTech Academy’s aim is to inspire, share and disseminate knowledge about the latest developments in quantum technology.\u003c/p\u003e376:T4f3,\u003cp\u003eIn this course we will demonstrate how a large-scale quantum computer could be controlled and operated. Among the topics that we will discuss are micro-architectures, compilers, and programming languages. The course will also cover some of the basics of quantum error-correction, an essential procedure that allows us to combat errors that arise during computations using delicate qubits, necessary for fault-tolerant quantum computing. To co"])</script><script>self.__next_f.push([1,"mplete the story arc from the hardware of quantum computers to their software, the course will discuss the main factors that triggered the efforts to build quantum computers in the first place: quantum algorithms.\u003c/p\u003e\n\u003cp\u003eThe course then concludes with a discussion on the quantum internet: what is it? How can it be built? Why is it useful?\u003c/p\u003e\n\u003cp\u003eThe course is a journey of discovery, so we encourage you to bring your own experiences, insights and thoughts via the forum!\u003c/p\u003e\n\u003cp\u003eThis course is authored by experts from the QuTech research center at Delft University of Technology. In the center, scientists and engineers work together to enhance research and development in quantum technology. QuTech Academy’s aim is to inspire, share and disseminate knowledge about the latest developments in quantum technology.\u003c/p\u003e377:T708,\u003cp\u003eThere is no doubt that quantum computers and the quantum internet will have a great impact on our world. But we don’t yet know quite how. As with traditional computers - we will only see the effects in the decades to come.\u003c/p\u003e\n\u003cp\u003eThis course will provide you with a basic understanding of quantum computing and the quantum internet. Together, we’ll peek into the fascinating world of quantum information, learning about qubits, superposition, entanglement, and much more.\u003c/p\u003e\n\u003cp\u003eWe’ll envision the potential impact of quantum computing and the quantum internet.\u003c/p\u003e\n\u003cp\u003eYou’ll explore various application areas, such as quantum chemistry, quantum machine learning, encryption and secure communication, factorization, and blind quantum computation.\u003c/p\u003e\n\u003cp\u003eThe course is aimed at a broad and diverse audience including policy-makers, people with a scientific or personal interest, business executives, and students at all levels. We invite you on a journey beyond what is known to us now, and to envision a world with quantum technologies.\u003c/p\u003e\n\u003cp\u003eThis journey continues with our program \u003ca href=\"https://www.edx.org/professional-certificate/delftx-quantum-computing-and-quantum-internet\" title=\"Quantum 101: Q"])</script><script>self.__next_f.push([1,"uantum Computing \u0026 Quantum Internet\"\u003e\u003cem\u003eQuantum 101: Quantum Computing and Quantum Internet\u003c/em\u003e\u003c/a\u003e, where we expand from an understanding of the building blocks of quantum computers to look at further applications and possibilities.\u003c/p\u003e\n\u003cp\u003eThis course is authored by experts from the QuTech research center at Delft University of Technology. In the center scientists and engineers work together to enhance research and development in quantum technology. QuTech Academy’s aim is to inspire, share and disseminate knowledge about the latest developments in quantum technology.\u003c/p\u003e378:T7f1,\u003cp\u003eQuantum supremacy is a term that refers to the projected ability of quantum computers to perform computations that are beyond the capabilities of any classical computer. The era that quantum computing promises to bring about is often likened to the era initiated by the classical computer. In such a \"quantum\" information era, quantum computers will be complemented by the quantum internet, which will allow for the transmission of quantum information over long distances. This capability would support many revolutionary applications, such as unhackable communication, clock synchronization and secure access to quantum computers in the cloud.\u003c/p\u003e\r\n\r\n\u003cp\u003eBut how do quantum computers and quantum internet work? What scientific principles are behind them? What is the hardware that is being researched? What kind of software and protocols are needed for quantum computing and quantum internet? Which disciplines of science and engineering are required to develop these?\u003c/p\u003e\r\n\r\n\u003cp\u003eThe aim of this program is to help you get up to speed with the present progresses in the transition to a quantum information era. After a quick review of some of the basic concepts that will enable you understanding the operating principles of quantum computation and quantum internet, the program will begin with an extensive discussion on some of the different ways qubits can be built.\u003c/p\u003e\r\n\r\n\u003cp\u003eMoreover, we will discuss how a large-scale quantum processor could be bui"])</script><script>self.__next_f.push([1,"lt using these qubits. Some of the topics that we cover are micro-architectures, compilers, and quantum programming languages. You will also explore some of the basics of quantum error-correction, an essential procedure that allows us to combat errors that arise during computations using delicate qubits.\u003c/p\u003e\r\n\r\n\u003cp\u003eThe program then concludes with a discussion on the quantum internet: what is it? How can it be built? Why is it useful?\u003c/p\u003e\r\n\r\n\u003cp\u003eThe program is a journey of discovery, so we encourage you to bring your own experiences, insights and thoughts via the forum!\u003c/p\u003e379:T7e7,\u003cp\u003e\u003cstrong\u003e\u003cem\u003eIf you have specific questions about this course, please contact us at\u003ca href=\"mailto:sds-mm@mit.edu\"\u003e sds-mm@mit.edu\u003c/a\u003e.\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMachine learning methods are commonly used across engineering and sciences, from computer systems to physics. Moreover, commercial sites such as search engines, recommender systems (e.g., Netflix, Amazon), advertisers, and financial institutions employ machine learning algorithms for content recommendation, predicting customer behavior, compliance, or risk.\u003c/p\u003e\n\u003cp\u003eAs a discipline, machine learning tries to design and understand computer programs that learn from experience for the purpose of prediction or control.\u003c/p\u003e\n\u003cp\u003eIn this course, students will learn about principles and algorithms for turning training data into effective automated predictions. We will cover:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eRepresentation, over-fitting, regularization, generalization, VC dimension;\u003c/li\u003e\n\u003cli\u003eClustering, classification, recommender problems, probabilistic modeling, reinforcement learning;\u003c/li\u003e\n\u003cli\u003eOn-line algorithms, support vector machines, and neural networks/deep learning.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eStudents will implement and experiment with the algorithms in several Python projects designed for different practical applications.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThis course is part of the\u003ca href=\"https://www.edx.org/micromasters/mitx-statistics-and-data-science\"\u003e MITx MicroMasters Program in Statistics and Data Science\u003c/a\u003e. Master the skills "])</script><script>self.__next_f.push([1,"needed to be an informed and effective practitioner of data science. You will complete this course and three others from MITx, at a similar pace and level of rigor as an on-campus course at MIT, and then take a virtually-proctored exam to earn your MicroMasters, an academic credential that will demonstrate your proficiency in data science or accelerate your path towards an MIT PhD or a Master's at other universities. To learn more about this program, please visit \u003ca href=\"https://micromasters.mit.edu/ds/\"\u003ehttps://micromasters.mit.edu/ds/\u003c/a\u003e.\u003c/strong\u003e\u003c/p\u003e37a:T73b,\u003cp\u003eThis course integrates the power of systems thinking with computer models designed to ‘bring to life’ biology topics including evolution, ecology and the chemistry of life. Developed in collaboration with the University of Pennsylvania Graduate School of Education and the Massachusetts Institute of Technology Scheller Teacher Education Program, this six-week interactive and collaborative professional development course draws on research in teaching and learning to develop the best experience for teachers.\u003c/p\u003e\n\u003cp\u003eIn this discussion-based course, you will learn how to use online simulations which are aligned with the Next Generation Science Standards in order to develop core biology content and practices. The student facing materials consist of five modules designed for implementation over several class periods, serving as a replacement for an existing lab or activity. The online simulations include optional entry-level coding and the course provides support for learning to teach this with students. The materials include student and teacher guides with built in informal assessments. You will get a chance to work through these materials, watch teachers experienced with the materials teach the lessons, and then interact with experienced BioGraph teachers through online forums, webinars, and expert facilitation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImportant Information Regarding Verified Certificates:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe BioGraph Team will cover the cost of the Verified Ce"])</script><script>self.__next_f.push([1,"rtificate for participants who complete the course, including all surveys. In order to be eligible for this benefit please DO NOT register for the Verified Certificate. Upon completing the course, you will be issued a coupon which will allow you to receive the certificate free of charge. We cannot issue refunds or reimbursements for personally purchased certificates.\u003c/p\u003e37b:T93a,"])</script><script>self.__next_f.push([1,"\u003cp\u003eAre you navigating through the maze of AI discussions in everyday conversations? Do you feel overwhelmed and find it challenging to keep up with the constant flow of AI news and hype? Or perhaps you are enthusiastic about AI and its transformative power in design practices. This course will shed light on the science behind the most popular AI tools and models.\u003c/p\u003e\n\u003cp\u003eAre you an architect concerned about the potential impact of AI on your role? If you're eager to upskill, this course is designed to help you manage expectations and enhance your skills, ensuring greater job competency in the evolving landscape of design, data and AI.\u003c/p\u003e\n\u003cp\u003eThe course goes beyond introducing AI as merely a tool but presents a new methodology for scientific design thinking. The course material gives you a vision on how to adjust your skills for a more secure job market competency.\u003c/p\u003e\n\u003cp\u003eThe content of the course is specifically suitable for architects in practice or architectural students searching for something outside of the architecture field, possibly gaining new skills in programming and AI to fit into more diverse job opportunities.\u003c/p\u003e\n\u003cp\u003eThe learning journey starts with learning about the history of AI and understanding machine learning as the science behind the AI technology. Further, the focus is established on computer vision as the “eye of AI” within the domain of architectural design. You will learn about the most prominent machine learning approaches in theory and in coding practice. You practice machine learning by using Python programming notebooks and exploring architectural design datasets. You will learn how to use AI to visualize your design data and upgrade your design storytelling.\u003c/p\u003e\n\u003cp\u003eYou will learn how to search for reliable content including data and AI models in the overwhelming landscape of opensource AI. You will be introduced to licence-free “backstage” AI by going behind the main-stream glossy AI products.\u003c/p\u003e\n\u003cp\u003eYou will also be introduced to algorithmic and data-driven thinking, data patterns, and the transformative power of learning systems. Hands-on experience with Python programming is included in the course. The assessments will include multiple choice quizzes, written text, and a a brief machine learning coding project that combines theory with real-world application and data practices.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"37c:T4f1,\u003cp\u003eData is at the heart of our digital economy and data science has been ranked as the hottest profession of the 21st century. Whether you are new to the job market or already in the workforce and looking to upskill yourself, this five course Data Science with Python Professional Certificate program is aimed at preparing you for a career in data science and machine learning. No prior computer programming experience required!\u003c/p\u003e\r\n\r\n\u003cp\u003eYou will start by learning Python, the most popular language for data science. You will then develop skills for data analysis and data visualization and also get a practical introduction in machine learning. Finally, you will apply and demonstrate your knowledge of data science and machine learning with a capstone project involving a real life business problem.\u003c/p\u003e\r\n\r\n\u003cp\u003eThis program is taught by experts and focused on hands-on learning and job readiness. As such you will work with real datasets and will be given no-charge access to tools like Jupyter notebooks in the IBM Cloud. You will utilize popular Python toolkits and libraries such as pandas, numpy, matplotlib, seaborn, folium, scipy, scikitlearn, and more.\u003c/p\u003e\r\n\r\n\u003cp\u003eStart developing data and analytical skills today and launch your career in data science!\u003c/p\u003e37d:T51a,\u003cp\u003eIn the information age, data is all around us. Within this data are answers to compelling questions across many societal domains (politics, business, science, etc.). But if you had access to a large dataset, would you be able to find the answers you seek?\u003c/p\u003e\n\u003cp\u003eThis course, part of the Data Science MicroMasters program, will introduce you to a collection of powerful, open-source, tools needed to analyze data and to conduct data science. Specifically, you'll learn how to use:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003epython\u003c/li\u003e\n\u003cli\u003ejupyter notebooks\u003c/li\u003e\n\u003cli\u003epandas\u003c/li\u003e\n\u003cli\u003enumpy\u003c/li\u003e\n\u003cli\u003ematplotlib\u003c/li\u003e\n\u003cli\u003egit\u003c/li\u003e\n\u003cli\u003eand many other tools.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eYou will learn these tools all within the context of solving compelling data science problems.\u003c/p\u003e\n\u003cp\u003eAfter completing this c"])</script><script>self.__next_f.push([1,"ourse, you'll be able to find answers within large datasets by using python tools to import data, explore it, analyze it, learn from it, visualize it, and ultimately generate easily sharable reports.\u003c/p\u003e\n\u003cp\u003eBy learning these skills, you'll also become a member of a world-wide community which seeks to build data science tools, explore public datasets, and discuss evidence-based findings. Last but not least, this course will provide you with the foundation you need to succeed in later courses in the Data Science MicroMasters program.\u003c/p\u003e37e:Tb9f,"])</script><script>self.__next_f.push([1,"\u003cp\u003eResearch has been traditionally viewed as a purely academic undertaking, especially in limited-resource healthcare systems. Clinical trials, the hallmark of medical research, are expensive to perform, and take place primarily in countries which can afford them. Around the world, the blood pressure thresholds for hypertension, or the blood sugar targets for patients with diabetes, are established based on research performed in a handful of countries. There is an implicit assumption that the findings and validity of studies carried out in the US and other Western countries generalize to patients around the world.\u003c/p\u003e\n\u003cp\u003eThis course was created by members of MIT Critical Data, a global consortium that consists of healthcare practitioners, computer scientists, and engineers from academia, industry, and government, that seeks to place data and research at the front and center of healthcare operations.\u003c/p\u003e\n\u003cp\u003eBig data is proliferating in diverse forms within the healthcare field, not only because of the adoption of electronic health records, but also because of the growing use of wireless technologies for ambulatory monitoring. The world is abuzz with applications of data science in almost every field – commerce, transportation, banking, and more recently, healthcare. These breakthroughs are due to rediscovered algorithms, powerful computers to run them, and most importantly, the availability of bigger and better data to train the algorithms. This course provides an introductory survey of data science tools in healthcare through several hands-on workshops and exercises.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eWho this course is aimed at\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe most daunting global health issues right now are the result of interconnected crises. In this course, we highlight the importance of a multidisciplinary approach to health data science. It is intended for front-line clinicians and public health practitioners, as well as computer scientists, engineers and social scientists, whose goal is to understand health and disease better using digital data captured in the process of care.\u003c/p\u003e\n\u003cp\u003eWe highly recommend that this course be taken as part of a team consisting of clinicians and computer scientists or engineers. Learners from the healthcare sector are likely to have difficulties with the programming aspect while the computer scientists and engineers will not be familiar with the clinical context of the exercises and workshops.\u003c/p\u003e\n\u003cp\u003eThe MIT Critical Data team would like to acknowledge the contribution of the following members: Aldo Arevalo, Alistair Johnson, Alon Dagan, Amber Nigam, Amelie Mathusek, Andre Silva, Chaitanya Shivade, Christopher Cosgriff, Christina Chen, Daniel Ebner, Daniel Gruhl, Eric Yamga, Grigorich Schleifer, Haroun Chahed, Jesse Raffa, Jonathan Riesner, Joy Tzung-yu Wu, Kimiko Huang, Lawerence Baker, Marta Fernandes, Mathew Samuel, Philipp Klocke, Pragati Jaiswal, Ryan Kindle, Shrey Lakhotia, Tom Pollard, Yueh-Hsun Chuang, Ziyi Hou.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"37f:T42b,\u003cp\u003e\u003cspan lang=\"EN-US\"\u003eIn part 2, we will dive down into the oceans that cover 70% of the planet to understand how the oceans impact our climate. We will visit the frozen parts of the Earth (the cryosphere), and the vegetated parts of our planet (the biosphere). How does the cryosphere impact sea level rise in the future? How does the biosphere impact carbon dioxide in the atmosphere? We will take a trip to a volcano to understand how large volcanic eruptions can also impact the Earth’s temperature. Could we produce an artificial volcano to offset global warming? After studying all the different important components of the climate system, we will learn how computer models put all this information together to estimate what may happen to our global and regional climates in 2050 or 2100. What are the various scenarios for the future? How accurate are these forecasts? And towards the end of the course, we will talk about what can be done to deal with the climate crisis. It is not all bad news. There are some very exciting solutions out there. \u003c/span\u003e\u003c/p\u003e380:Tb68,"])</script><script>self.__next_f.push([1,"\u003cul\u003e\n\u003cli\u003e\u003cstrong\u003e\u003cem\u003e\u003cspan lang=\"EN-US\"\u003eThe Oceans\u003c/span\u003e\u003c/em\u003e\u003c/strong\u003e\u003cspan lang=\"EN-US\"\u003e : Oceans cover 70% of the area of the Earth, and hence have a huge impact on the \u003c/span\u003e\u003cspan lang=\"EN\"\u003eclimate\u003c/span\u003e\u003cspan lang=\"EN-US\"\u003e of the Earth. The \u003c/span\u003e\u003cspan lang=\"EN\"\u003eocean\u003c/span\u003e\u003cspan lang=\"EN-US\"\u003e currents, temperatures, and absorption of carbon dioxide are all key features that influence the global \u003c/span\u003e\u003cspan lang=\"EN\"\u003eclimate\u003c/span\u003e\u003cspan lang=\"EN-US\"\u003e. \u003c/span\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003e\u003cspan lang=\"EN-US\"\u003eThe Cryosphere\u003c/span\u003e\u003c/strong\u003e\u003cspan lang=\"EN-US\"\u003e : Some parts of the planets are always frozen below 0C. These include glaciers, \u003c/span\u003e\u003cspan lang=\"EN\"\u003esea ice\u003c/span\u003e\u003cspan lang=\"EN-US\"\u003e, \u003c/span\u003e\u003cspan lang=\"EN\"\u003eland\u003c/span\u003e\u003cspan lang=\"EN-US\"\u003e ice and \u003c/span\u003e\u003cspan lang=\"EN\"\u003epermafrost\u003c/span\u003e\u003cspan lang=\"EN-US\"\u003e regions (\u003c/span\u003e\u003cspan lang=\"EN\"\u003efrozen ground\u003c/span\u003e\u003cspan lang=\"EN-US\"\u003e). The \u003c/span\u003e\u003cspan lang=\"EN\"\u003ecryosphere\u003c/span\u003e\u003cspan lang=\"EN-US\"\u003e is responding dramatically to rising temperatures, with \u003c/span\u003e\u003cspan lang=\"EN\"\u003eimpacts\u003c/span\u003e\u003cspan lang=\"EN-US\"\u003e on sea level rise, \u003c/span\u003e\u003cspan lang=\"EN\"\u003eocean\u003c/span\u003e\u003cspan lang=\"EN-US\"\u003e currents and global temperatures. \u003c/span\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003e\u003cspan lang=\"EN-US\"\u003eThe Biosphere\u003c/span\u003e\u003c/strong\u003e\u003cspan lang=\"EN-US\"\u003e : Vegetation around the planet also has an important role in modulating the Earth’s \u003c/span\u003e\u003cspan lang=\"EN\"\u003eclimate\u003c/span\u003e\u003cspan lang=\"EN-US\"\u003e. Both on \u003c/span\u003e\u003cspan lang=\"EN\"\u003eland\u003c/span\u003e\u003cspan lang=\"EN-US\"\u003e and in the oceans plants absorb CO2 via \u003c/span\u003e\u003cspan lang=\"EN\"\u003ephotosynthesis\u003c/span\u003e\u003cspan lang=\"EN-US\"\u003e, while also impacting \u003c/span\u003e\u003cspan lang=\"EN\"\u003eland\u003c/span\u003e\u003cspan lang=\"EN-US\"\u003e temperatures, \u003c/span\u003e\u003cspan lang=\"EN\"\u003ealbedo\u003c/span\u003e\u003cspan lang=\"EN-US\"\u003e and moisture balance. \u003c/span\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003e\u003cspan lang=\"EN-US\"\u003eVolcanoes\u003c/span\u003e\u003c/strong\u003e\u003cspan lang=\"EN-US\"\u003e : While volcanoes may not seem relevant to the discussion about \u003c/span\u003e\u003cspan lang=\"EN\"\u003eclimate change\u003c/span\u003e\u003cspan lang=\"EN-US\"\u003e, we know that large volcanic eruptions in the past have resulted in a significant cooling of global temperatures. Hence, we need to understand the science behind this global cooling. \u003c/span\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003e\u003cspan lang=\"EN-US\"\u003eClimate Forecasts\u003c/span\u003e\u003c/strong\u003e\u003cspan lang=\"EN-US\"\u003e : After understanding the different key aspects of the \u003c/span\u003e\u003cspan lang=\"EN\"\u003eclimate system\u003c/span\u003e\u003cspan lang=\"EN-US\"\u003e, we can now discuss global \u003c/span\u003e\u003cspan lang=\"EN\"\u003eclimate\u003c/span\u003e\u003cspan lang=\"EN-US\"\u003e models and how they are used to simulate the \u003c/span\u003e\u003cspan lang=\"EN\"\u003eclimate system\u003c/span\u003e\u003cspan lang=\"EN-US\"\u003e (past, present, and future). What are the scenarios for 2100?\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003e\u003cspan lang=\"EN-US\"\u003eSolutions\u003c/span\u003e\u003c/strong\u003e\u003cspan lang=\"EN-US\"\u003e : Finally, after understanding the problem we face, we can also address the possible solutions. What is the road map to get to net-zero emissions by 2050? Can we do it? What are the alternatives?\u003c/span\u003e\u003c/li\u003e\n\u003c/ul\u003e"])</script><script>self.__next_f.push([1,"381:T8ed,"])</script><script>self.__next_f.push([1,"\u003cp\u003eDo you have an interest in biology and quantitative tools? Do you know computational methods but do not realize how they apply to biological problems? Do you know biology but do not understand how scientists really analyze complicated data? 7.QBWx: Quantitative Biology Workshop is designed to give learners exposure to the application of quantitative tools to analyze biological data at an introductory level. The Biology Department of MIT has run this workshop-style course as part of a one-week outreach program for students from other universities. With 7.QBWx, we can give more learners from around the world the chance to discover quantitative biology. We hope that this series of workshops encourages learners to explore new interests and take more biology and computational courses.\u003c/p\u003e\n\u003cp\u003eWe expect that learners from 7.00x Introduction to Biology - The Secret of Life or an equivalent course can complete this workshop-based course without a background in programming. The course content will introduce programming languages but will not teach any one language in a comprehensive manner. The content of each week varies. We want learners to have an introduction to multiple languages and tools to find a topic that they would want to explore more. We recommend that learners try to complete each week to find what interests them the most. \u003c/p\u003e\n\u003cp\u003eThis workshop includes activities on the following biological topics: population biology, biochemical equilibrium and kinetics, molecular modeling of enzymes, visual neuroscience, global and single-cell gene expression, development, and genomics. The tools and programming languages include MATLAB, PyMOL, Python, and R. This course does not require learners to download MATLAB. All MATLAB activities run and are graded within the edX platform. We do recommend that participants download a few other free tools for the activities so that they learn how to use the same tools and programs that scientists use.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eWorkshop Content Creators and Residential Leaders\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eGregory Hale, Michael Goard, Ben Stinson, Kunle Demuren, Sara Gosline, Glenna Foight, Leyla Isik, Samir El-Boustani, Gerald Pho, and Rajeev Rikhye\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eResidential Outreach Workshop Organizer and Creator\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMandana Sassanfar\u003c/p\u003e"])</script><script>self.__next_f.push([1,"382:T4af,\u003cp\u003eExcel in Data Science, one of the hottest fields in tech today. Learn how to gain new insights from big data by asking the right questions, manipulating data sets and visualizing your findings in compelling ways. \u003c/p\u003e \r\n\r\n\u003cp\u003eIn this MicroMasters program, you will develop a well-rounded understanding of the mathematical and computational tools that form the basis of data science and how to use those tools to make data-driven business recommendations. \u003c/p\u003e \r\n\r\n\u003cp\u003eThis MicroMasters program encompasses two sides of data science learning: the mathematical and the applied. \u003c/p\u003e \r\n\r\n\u003cp\u003eMathematical courses cover probability, statistics, and machine learning. The applied courses cover the use of specific toolkit and languages such as Python, Numpy, Matplotlib, pandas and Scipy, the Jupyter notebook environment and Apache Spark to delve into real world data.\u003c/p\u003e \r\n\r\n\u003cp\u003eYou will learn how to collect, clean and analyse big data using popular open source software will allow you to perform large-scale data analysis and present your findings in a convincing, visual way. When combined with expertise in a particular type of business, it will make you a highly desirable employee.\u003c/p\u003e383:T9b7,"])</script><script>self.__next_f.push([1,"\u003cp\u003eThis course focuses on the scientific background of the present-day climate crisis, often also called Global Warming. The course will give you the scientific knowledge and tools needed to understand the crisis, including the many uncertainties behind the science. What do we really know with great certainty, and what is less certain? Can we still act given the uncertainty in the science behind the climate crisis?\u003c/p\u003e\r\n \r\n\u003cp\u003eAfter a short introduction to global warming, we will go back in time and put the present changes occurring today in context, by looking back in time to the ice ages that have occurred on our planet over the past million years.\u003c/p\u003e \r\n\r\n\u003cp\u003eAre the changes happening today really that unusual? Have similar changes occurred in the past? We will then focus our weekly discussions on key aspects of the climate system to better understand the complexity of our climate. We will take a journey to our Sun, the source of all our energy in the climate system. Can the changes in our Sun explain the recent global warming? We will discuss the Energy Balance of our planet resulting from the balance between the energy we get from the Sun, and the energy lost from the Earth by cooling. We will learn about the water cycle and the important role of clouds and rain in the climate system. How do clouds impact the Earth’s temperature? We will discuss atmospheric circulation patterns, winds and storms.\u003c/p\u003e \r\n\r\n\u003cp\u003eThen we will dive down into the oceans that cover 70% of the planet to understand how the oceans impact our climate. We will visit the frozen parts of the Earth (the cryosphere), and the vegetated parts of our planet (the biosphere). How does the cryosphere impact sea level rise in the future? How does the biosphere impact carbon dioxide in the atmosphere? We will take a trip to a volcano to understand how large volcanic eruptions can also impact the Earth’s temperature. Could we produce an artificial volcano to offset global warming?\u003c/p\u003e \r\n\r\n\u003cp\u003eAfter studying all the different important components of the climate system, we will learn how computer models put all this information together to estimate what may happen to our global and regional climates in 2050 or 2100. What are the various scenarios for the future? How accurate are these forecasts? And towards the end of the course, we will talk about what can be done to deal with the climate crisis. It is not all bad news. There are some very exciting solutions out there.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"384:T736,\u003cp\u003eGive your career a boost by mastering the advanced concepts underpinning the design of multicore-based computers. This professional certificate program covers design principles governing modern microprocessors, such as pipelining, cache memories, parallelism, prefetching, and cache coherency. Applying these concepts is critical when developing competitive computerized products. Take, for instance, a smartphone with limited battery capacity. Improved functionality can lead to significantly shorter operation time between battery charges, thus utilizing the already limited resources of a smartphone far more efficiently.\u003c/p\u003e\r\n\r\n\u003cp\u003eThe target audience for this program is practicing software and hardware engineers in need of a deep understanding of performance engineering. This program is also well suited for students who want to specialize in computer engineering and get a deep understanding of the working of modern computers.\u003c/p\u003e\r\n\r\n\u003cp\u003eThis program is derived from both undergraduate and advanced graduate courses in computer system design. It starts on a basic level and then gradually introduces more advanced concepts. The program offers a unique opportunity to learn about computer systems on a machine and assembly language level.\u003c/p\u003e\r\n\r\n\u003cp\u003eThe courses are given by Per Stenström, a world-renowned research leader in computer architecture. He is a Fellow of ACM and IEEE and member of three academies (Royal Swedish Academy of Engineering Science, The European Academy, and the Royal Spanish Academy of Engineering Science). He has co-authored around 200 publications and 20 patents and has co-founded a few high-tech startup companies.\u003c/p\u003e\r\n\r\n\u003cp\u003eBy the end of this program, you will have a deep understanding in the design of future multicore-based computers and the impact on energy efficiency and program execution time.\u003c/p\u003e385:T444,\u003cp\u003eDigital Design is about designing in digital space so the created content can be displayed and seen on a digital device. With the availability of high computing power, designers can"])</script><script>self.__next_f.push([1," quickly create designs in digital space before actual deployment.\u003c/p\u003e\n\u003cp\u003eIn this online course, you will learn the fundamental concepts of a wide variety of digital design technology and you will have the opportunity to create your own digital designs and animate them as well. The course focuses on \u003cstrong\u003ecreating 3D objects\u003c/strong\u003e using a computer-aided design package, \u003cstrong\u003ecreating real-life physical simulations,\u003c/strong\u003e and then \u003cstrong\u003ecombining the two techniques to create rendered animations\u003c/strong\u003e. It will also \u003cstrong\u003eintroduce virtual reality (VR) and augmented reality (AR) applications\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eThis course allows you to get hands-on experience with different design tools so that the various outputs can be combined in a systematic way. So get started to experience this excitement of creating your own designs now whether it be for continuing education or as a hobby.\u003c/p\u003e386:T91d,"])</script><script>self.__next_f.push([1,"\u003cp\u003eDigital systems have revolutionized our world. From television to cell phones to GPS to warfare to automobiles to medicine to distance education, computers and digital processing have reshaped the way we live and work. The semiconductor industry has grown from $21B in 1985 to $412B in 2019, making it one of the largest sectors of the economy. Computers are also a vital part of daily practice in every field of science and engineering.\u003c/p\u003e\n\u003cp\u003ePrevious generations of engineers learned the “nuts and bolts” of the profession by doing hand-on projects such as disassembling and rebuilding engines. As technology has advanced, cars have become too complicated for the average person to work on. Ironically, the same advances have made computers much easier to build. While most fields of engineering require extensive mathematics and complicated analysis of even rather simple components, digital systems merely require counting from 0 to 1. Their challenge, instead, is in combining many simple building blocks into a complex whole. In this class, you will experiment with digital systems, building simple circuits from logic gates on a breadboard and designing more complex systems with a logic simulator. You will learn how to systematically create digital systems with a desired function. By the end of this course, you will have the knowledge and experience to design digital systems and be prepared for more advanced coursework.\u003c/p\u003e\n\u003cp\u003eBeyond the practical reasons to take this class, I hope you find it enormously fun and exciting like I do. There's a great satisfaction about being able to build things. Digital systems are ideal because the components are far cheaper and easier to use than in other engineering fields. It's also amazing to demystify how digital systems work under the hood. I fell in love with digital design when I first studied it in college, and I hope you do too!\u003c/p\u003e\n\u003cp\u003eThis is the first half of a 2-part sequence. This half covers digital design. The second half, ENGR85B, covers computer architecture, where you will learn to program, use, and build microprocessors. By the end of the second half, you will have designed your own microprocessor and understand it all the way from the transistor level to the software. You'll also have built smart gadgets and games with lights and sensors.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"387:T794,\u003cp\u003eWildfires are a natural and essential part of our ecosystem, recycling soil nutrients and renewing healthy forests. In Alaska, around one million acres (4000 km2) burn every year, and record years have seen as many as six million acres burned. Most of these fires are allowed to spread naturally.\u003c/p\u003e\n\u003cp\u003eHowever, when wildfires occur near population centers, they can be a serious threat to the safety and well-being of people. Recent disastrous fire seasons in Alaska, California, and Australia have shown how communities near forests, in what is known as the Wildland Urban Interface (WUI), are increasingly at risk due to hotter and drier summer weather caused by climate change.\u003c/p\u003e\n\u003cp\u003eIn the fight to protect these communities, remote sensing technology has become essential. Wildfire analysts use satellite imagery and powerful computer programs to predict fire risk, detect fires early, and monitor their spread. After a wildfire is extinguished, remote sensing is used to analyze the impact of a fire and to guide sustainable restoration efforts.\u003c/p\u003e\n\u003cp\u003eParticipants in this course will learn about remote sensing of wildfires from instructors at the University of Alaska Fairbanks, located in one of the world’s most active wildfire zones. Students will learn about wildfire behavior, and get hands-on experience with tools and resources used by professionals to create geospatial maps that support firefighters on the ground.\u003c/p\u003e\n\u003cp\u003eUpon completion, students will be able to:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eAccess web resources that provide near real-time updates on active wildfires\u003c/li\u003e\n\u003cli\u003eNavigate databases of remote sensing imagery and data\u003c/li\u003e\n\u003cli\u003eAnalyze geospatial data to detect fire hot spots, map burn areas, and assess severity\u003c/li\u003e\n\u003cli\u003eProcess image and GIS data in ArcGIS Pro\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eVerified track learners will receive a one-year ArcGIS Pro license in addition to unlimited course access and a verified certificate.\u003c/p\u003e388:T65f,\u003cp\u003eLearn from a dynamic team of 25 dental practitioners and researchers across 10 dental s"])</script><script>self.__next_f.push([1,"pecialties from around the world led by HKU’s Professor Jukka P. Matinlinna and Dr James K.H. Tsoi. In this 4-Week-4-Module course, Digital Biomaterials, you will not only learn the special properties of novel biomaterials in oral health care, but you will be introduced to the crucial and dramatic roles of digital dentistry in contemporary oral health care.\u003c/p\u003e\n\u003cp\u003eNew technology development and breakthroughs in biomaterials research have transformed oral health care. The discoveries of the special properties of biomaterials such as titanium, zirconia and various polymeric composite materials have led to the rapid development of more versatile, durable and safe materials, offering oral health care that meet patients’ treatment needs and aesthetic restorative results. In recent years, advancement in digital dentistry such as CAD/CAM technology in crown fabrication, 3D printing, artificial intelligence, stereophotogrammetry and digital orthodontics have greatly impacted many aspects of oral health care, in particular, oral and maxillofacial surgery, implant dentistry and regenerative medicine.\u003c/p\u003e\n\u003cp\u003eOral biomaterials research today is an exciting and intensive multidisciplinary area that encompasses contributions from a wide range of fields from clinical dentistry to biology, chemistry, physics, material science, and engineering. We cordially invite those of you who wish to make a difference in tomorrow’s dental materials and oral health development to join us in the exciting journey in Digital Biomaterials.\u003c/p\u003e389:Tb12,"])</script><script>self.__next_f.push([1,"\u003cp\u003eThe course Digital Biomaterials compiles four modules introducing the most cutting-edge digital and computer technologies in dentistry including big data, artificial intelligence (AI), and digital workflow that support clinical dental diagnostics, and enhance the efficiency of fabricating durable dental restorations. Learners will also be introduced to the properties of the most commonly used dental materials such as titanium, various ceramics and composite biomaterials.. Furthermore, adhesion of dissimilar materials to tooth structures will also be explained.\u003c/p\u003e\n\u003cp\u003eThe learning objectives of the four modules in Digital Biomaterials are as follows:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eModule 1\u003c/em\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eDefine what digital dentistry is and what it includes.\u003c/li\u003e\n\u003cli\u003eExamine the clinical implications of dental imaging, 3D-stereophotogrammetry, intraoral scanner and cone-beam computerized tomography (CBCT).\u003c/li\u003e\n\u003cli\u003eCompare and contrast CAD/CAM with conventional techniques in dentistry.\u003c/li\u003e\n\u003cli\u003eUnderstand the role of digital dentistry in areas of orthodontics, oral and maxillofacial surgery (OMFS).\u003c/li\u003e\n\u003cli\u003eExamine commonly used digital techniques in dentistry such as impression taking, shade matching, radiography, and 3D printing.\u003c/li\u003e\n\u003cli\u003eAppreciate the role of digital technology in shaping the future of dentistry .\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cem\u003eModule 2\u003c/em\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eUnderstand the basic science behind applications of titanium in dentistry and what matters on the titanium surface.\u003c/li\u003e\n\u003cli\u003eAppraise the special properties and implications of ceramics in dental materials.\u003c/li\u003e\n\u003cli\u003eLearn the surface treatment methods of zirconia.\u003c/li\u003e\n\u003cli\u003eCompare and contrast the advantages and shortcomings of zirconia against titanium.\u003c/li\u003e\n\u003cli\u003eUnderstand the clinical purpose, principles and techniques to treat surfaces (grit blasting and acid-etching).\u003c/li\u003e\n\u003cli\u003eUnderstand the applications of silicon and related compounds in dentistry.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cem\u003eModule 3\u003c/em\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eIdentify and list computer technologies used in dentistry.\u003c/li\u003e\n\u003cli\u003eDescribe the digital workflow in dental applications.\u003c/li\u003e\n\u003cli\u003eDiscuss the computer technologies applied in the field of digital orthodontics.\u003c/li\u003e\n\u003cli\u003eApprehend and justify the use of big data and artificial intelligence technology in dentistry - is it the future of dentistry? \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cem\u003eModule 4\u003c/em\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eUnderstand the design and chemistry of fibre-reinforced composite materials.\u003c/li\u003e\n\u003cli\u003eCompare and contrast fibre-reinforced composites with conventional biomaterials.\u003c/li\u003e\n\u003cli\u003eDefine and classify the whole spectrum of dental cements.\u003c/li\u003e\n\u003cli\u003eExamine the properties, chemistry and applications of tricalcium silicate-based cements in endodontology.\u003c/li\u003e\n\u003cli\u003eAppraise the compositions, indications and applications of dentin bonding materials and systems.\u003c/li\u003e\n\u003c/ul\u003e"])</script><script>self.__next_f.push([1,"38a:T5f4,\u003cp\u003eEngage in this course pertaining to a highly impactful yet, too rarely discussed, AI-related topic. You will learn from international experts in the field, also speakers at IVADO’s International School on Bias and Discrimination in AI, which took place in Montreal, and explore the social and technical aspects of bias, discrimination and fairness in machine learning and algorithm design.\u003c/p\u003e\n\u003cp\u003eThe main focus of this course is: gender, race and socioeconomic-based bias as well as bias in data-driven predictive models leading to decisions. The course is primarily intended for professionals and academics with basic knowledge in mathematics and programming, but the rich content will be of great use to whomever uses, or is interested in, AI in any other way. These sociotechnical topics have proven to be great eye-openers for technical professionals!\u003c/p\u003e\n\u003cp\u003eThe total duration of the video content available in this course is 7:30 hours, cut into relevant segments that you may watch at your own pace. 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Throughout the courses, students will explore the art and science of cartography, focusing on the principles and techniques essential for effective map communication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLearning Objectives:\u003c/strong\u003e\u003c/p\u003e\n\u003col\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eExamine the Art and Science of Cartography\u003c/strong\u003e :\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eUnderstand the fundamental principles and history of cartography.\u003c/li\u003e\n\u003cli\u003eAnalyze the key components that contribute to effective map communication, including scale, projection, and symbolization.\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eCreate Vector Map Data from Raster Maps\u003c/strong\u003e :\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eLearn to convert raster map data into vector formats.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eDevelop skills in organizing and managing geospatial data within a geodatabase.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eDesign Choropleth Maps\u003c/strong\u003e :\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eMaster the creation of choropleth maps to visually represent spatial data.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eApply appropriate data classification techniques and symbology to convey clear and accurate information.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eDevelop Graduated Symbol Maps\u003c/strong\u003e :\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eCreate graduated symbol maps to represent varying data magnitudes.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eImplement effective data classification techniques and symbology for enhanced visual interpretation.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eConstruct Isarithmic Maps\u003c/strong\u003e :\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eLearn to produce isarithmic maps to illustrate continuous data surfaces.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eUtilize appropriate data classification techniques and symbology for accurate representation of phenomena.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eRender 3D Digital Elevation Models (DEMs)\u003c/strong\u003e :\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eTransform DEMs into 3D visualizations for advanced geospatial analysis.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003ePerform viewshed and line of sight calculations to assess visibility and spatial relationships in a three-dimensional context.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eBy the end of this two-part series, students will have a thorough understanding of cartographic principles and will be proficient in using various mapping techniques to create informative and visually compelling maps. Whether you're a novice or an experienced GIS professional, this course will enhance your ability to communicate spatial information effectively through innovative and precise map design.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"38c:Ta13,"])</script><script>self.__next_f.push([1,"\u003cp\u003eDive into the dynamic world of cartography with our comprehensive course, \"Planet Earth and Geovisualization.\" This two-part series is designed to equip students with both theoretical knowledge and practical skills in modern map-making and geospatial analysis. Throughout this course, students will explore the art and science of cartography, focusing on the principles and techniques essential for effective map communication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLearning Objectives:\u003c/strong\u003e\u003c/p\u003e\n\u003col\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eExamine the Art and Science of Cartography\u003c/strong\u003e :\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eUnderstand the fundamental principles and history of cartography.\u003c/li\u003e\n\u003cli\u003eAnalyze the key components that contribute to effective map communication, including scale, projection, and symbolization.\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eCreate Vector Map Data from Raster Maps\u003c/strong\u003e :\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eLearn to convert raster map data into vector formats.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eDevelop skills in organizing and managing geospatial data within a geodatabase.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eDesign Choropleth Maps\u003c/strong\u003e :\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eMaster the creation of choropleth maps to visually represent spatial data.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eApply appropriate data classification techniques and symbology to convey clear and accurate information.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eDevelop Graduated Symbol Maps\u003c/strong\u003e :\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eCreate graduated symbol maps to represent varying data magnitudes.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eImplement effective data classification techniques and symbology for enhanced visual interpretation.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eConstruct Isarithmic Maps\u003c/strong\u003e :\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eLearn to produce isarithmic maps to illustrate continuous data surfaces.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eUtilize appropriate data classification techniques and symbology for accurate representation of phenomena.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eRender 3D Digital Elevation Models (DEMs)\u003c/strong\u003e :\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eTransform DEMs into 3D visualizations for advanced geospatial analysis.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003ePerform viewshed and line of sight calculations to assess visibility and spatial relationships in a three-dimensional context.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eBy the end of this course, students will have a thorough understanding of cartographic principles and will be proficient in using various mapping techniques to create informative and visually compelling maps. Whether you're a novice or an experienced GIS professional, this course will enhance your ability to communicate spatial information effectively through innovative and precise map design.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"38d:T5d7,\u003cp\u003eQuantum technology is all around yet many of us can readily be confused by the science, let alone the trajectories to identifying commercial opportunities. Dominant in the hype is the emerging promise of quantum computing, still some way from delivering a useful and fully capable quantum computer. In such a context, making strategic decisions when the science and engineering are shifting presents many innovation dilemmas!\u003c/p\u003e\n\u003cp\u003eThis course applies a focus on quantum technologies that deliver innovative new products and services. The now ubiquitous mobile telephone demonstrates such innovation. Our interest lies in exploring enough of the science to boost our understanding so that we can make informed decisions to allocate resources that create and harness emerging opportunities. Such resource-allocation processes will be as many and varied as there are innovators to pursue them.\u003c/p\u003e\n\u003cp\u003eThe full 4-module course specifically targets strategic decision makers across the quantum domains of sensing, communication, and computing. The online course includes content from world-recognised quantum scientists as well as the approaches of practitioners seeking to harness the exciting technological potentials for their organizations and customers. The key artefact learners will develop is a quantum strategy for their own organization, identifying the enablers and challenges to unique opportunities. This quantum strategy can then serve as a roadmap for an innovation portfolio.\u003c/p\u003e38e:Tc3f,"])</script><script>self.__next_f.push([1,"\u003cp\u003eCurrently, countries around the world have launched their own brain plans and listed neuroscience research as a strategic development direction. For example, in 2013, the United States launched the BRAIN Initiative (Brain Research through Advancing Innovative Neurotechnologies, carrying out brain research through promoting innovative neurotechnologies) plan; in 2021, China launched Science and Technology Innovation 2030 - a major plan for \"brain science and brain-inspired research\". \"Neurophotonics\" came into being and has developed rapidly in recent years, becoming an emerging cutting-edge interdisciplinary subject. Neurophotonics research will not only help reveal the laws of brain cognitive development and provide evidence for disease diagnosis and treatment, but will also promote the development of brain-computer interfaces, artificial intelligence and other fields. However, there are no relevant monographs in the world that systematically introduce this emerging discipline.\u003c/p\u003e\n\u003cp\u003eSince the fall semester of 2018, Tsinghua University has launched the \"Neurophotonics\" course for graduate students (or senior undergraduates) in optical engineering, biomedical engineering and other majors to introduce \"Neurophotonics\" to graduate students or senior undergraduates in related majors. \"Study\" biological background knowledge, related research techniques, and explore future development directions.\u003c/p\u003e\n\u003cp\u003e\"Neurophotonics\" is a discipline that uses optical technology to carry out neuroscience research. The content mainly includes the use of optical technology to image neural structure and function and the use of optical technology to control neural activity. This course starts from the significance and methods of brain science research and introduces the irreplaceable advantages of neurophotonics research. It then discusses tissue optics and introduces the rules of light propagation in neural tissue based on the basic knowledge of neurobiology. Then, it starts from linear The two aspects of optics and nonlinear optics introduce neural structure and functional imaging technology; in addition, a neural activity manipulation technology - optogenetics technology is introduced; finally, the current research hotspots and future development directions of neurophotonics are discussed.\u003c/p\u003e\n\u003cp\u003eThis course is designed to introduce neuroscience to graduate students or senior undergraduates majoring in optical engineering, biomedical engineering, etc., and discuss new optical technologies and their application prospects in brain science research. It can also be used for graduate students majoring in neurobiology. Fundamentals of commonly used optical techniques provide opportunities. Through the study of this course, students can enhance their theoretical foundation and practical ability in the interdisciplinary subject of neurophotonics.\u003c/p\u003e\n\u003cp\u003eWith the funding of the Tsinghua University Graduate Education and Teaching Reform Project (2019), this course has accumulated relevant course recording materials, which are now shared here in the hope of exchange and learning with peers and experts.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"38f:T580,\u003cp\u003eHow do you create realistic animations? How do you predict the motion of materials? It’s key to the success of animated films to ensure (was insure) audiences believe in characters.\u003c/p\u003e\n\u003cp\u003eThis course will show you how to create lifelike animations focusing on the technical aspects of CGI animation and also give you a glimpse into how studios approach the art of physically-based animation.\u003c/p\u003e\n\u003cp\u003eYou will learn the fundamental concepts of physical simulation, including:\u003c/p\u003e\n\u003col\u003e\n\u003cli\u003eintegration of ordinary differential equations such as those needed to predict the motion of a dress in the wind.\u003c/li\u003e\n\u003cli\u003eformulation of models for physical phenomena such as crumpling sheet metal and flowing water.\u003c/li\u003e\n\u003cli\u003etreatment of discontinuities such as fractures and collisions.\u003c/li\u003e\n\u003cli\u003esimulation of liquids and solids in both Lagrangian and Eulerian coordinates.\u003c/li\u003e\n\u003cli\u003eartistic control of physically-based animations.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThese concepts will be put into practice in the programming assignments spanning:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eDiscretizing and integrating Newton’s equations of motion\u003c/li\u003e\n\u003cli\u003eConstrained Lagrangian Mechanics\u003c/li\u003e\n\u003cli\u003eCollisions, contact, and friction: detection and response\u003c/li\u003e\n\u003cli\u003eContinuum mechanics\u003c/li\u003e\n\u003cli\u003eFinite elements\u003c/li\u003e\n\u003cli\u003eRigid body simulation\u003c/li\u003e\n\u003cli\u003eThin shell and cloth simulation\u003c/li\u003e\n\u003cli\u003eElastic rod and hair simulation\u003c/li\u003e\n\u003cli\u003eFluid simulation\u003c/li\u003e\n\u003c/ul\u003e390:T650,\u003cp\u003eQuantum mechanics courses typically require you to learn a lot of high-level math in addition to the science, making it challenging to absorb and apply quantum ideas. Students often take these classes multiple times before they even begin to understand. In this course, we teach quantum mechanics in a representation-independent fashion that focuses on operators. The prerequisite math is lower, and we need to develop less of it. This allows us to focus on developing conceptual understanding and on relating quantum ideas to real experiments. We are amidst the second quantum revolution, where we observe and manipula"])</script><script>self.__next_f.push([1,"te individual quanta. This has ushered in the new field of quantum information science, with its three pillars of quantum computing, quantum communication and quantum sensing. This course will prepare you best for the quantum sensing side of quantum information science. You will even learn enough quantum mechanics to understand how the laser interferometry gravitational wave observatory works---one of the engineering marvels of humankind. Prerequisites: The three-semester calculus sequence and a math methods course are required. Freshman physics and modern physics are recommended. This course is appropriate for those with backgrounds in physics, chemistry, and engineering who are interested in learning quantum mechanics with a focus on applications to quantum sensing.\u003c/p\u003e\n\u003cp\u003eGeorgetownX currently offers a \u003ca href=\"https://www.edx.org/course/mathematical-and-computational-methods\" title=\"Mathematical and Computational Methods\"\u003eMathematical and Computational Methods\u003c/a\u003e course.\u003c/p\u003e391:T410,\u003cp\u003eThe course is broken into four parts, covering the following areas: \u003c/p\u003e\n\u003cp\u003e(i) conceptual ideas;\u003c/p\u003e\n\u003cp\u003e(ii) technical developments for working with operators; \u003c/p\u003e\n\u003cp\u003e(iii) applications to experiment;\u003c/p\u003e\n\u003cp\u003e(iv) applications to sensing. \u003c/p\u003e\n\u003cp\u003eIt begins with conceptual ideas associated with spins and light, which allow us to discuss complex phenomena, such as Bell experiments, nondemolition experiments, and photon bunching. Then we develop the formal methods needed to work with operators, including four fundamental operator identities. Next, we apply the formal developments to quantum problems, employing the Schr\\\"odinger factorization method and relating to many quantum experiments. We end by describing how single photons are detected, what a squeezed vacuum is and how LIGO can measure distances small enough that it can detect gravitational waves. The conceptual part is supplemented by over 50 computer-based simulations and animations. Each week has a robust problem set. There are two midterms and one final exam.\u003c/p\u003e392:T"])</script><script>self.__next_f.push([1,"7e9,\u003cp\u003eIn this hands-on course, you will learn how to use R Shiny to create data-driven web applications. By the end of the course, you will have created an interactive web application that highlights the biodiversity of America's National Parks. Your application will feature an interactive map, biodiversity calculator, trail journal and species images. Using R Shiny, you will expand your data analysis and visualization skills while developing a way to share and distribute your findings in an application. If you are a beginner level data professional, a student, a researcher, an academic marketing analyst, business and data analyst, or financial analyst, this course is for you.\u003c/p\u003e\n\u003cp\u003eThis four week course will give you a foundation for making and deploying Shiny applications. Along the way you will learn about user interaction (UI) controls, persistent data storage using google sheets, customizing your application with CSS and publishing through \u003ca href=\"https://nam10.safelinks.protection.outlook.com/?url=http%3A%2F%2Fshinyapps.io%2F\u0026data=05%7C01%7Cevrozantes%40davidson.edu%7Ccc3834d714ad43ad7b9b08da643912a1%7C35d8763cd2b14213b629f5df0af9e3c3%7C1%7C0%7C637932493544897146%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C\u0026sdata=8Jqk0GuvS%2BfTZptHfKu7kQR5b34QJxAPAf8iTlVHgi4%3D\u0026reserved=0\"\u003eshinyapps.io\u003c/a\u003e. You will create your own unique application(s) that you can share with friends, colleagues, and potential employers.\u003c/p\u003e\n\u003cp\u003eCourse Requirement: Computer that can run R/RStudio - \u003ca href=\"https://nam10.safelinks.protection.outlook.com/?url=http%3A%2F%2Fshinyapps.io%2F\u0026data=05%7C01%7Cevrozantes%40davidson.edu%7Ccc3834d714ad43ad7b9b08da643912a1%7C35d8763cd2b14213b629f5df0af9e3c3%7C1%7C0%7C637932493544897146%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C\u0026sdata=8Jqk0GuvS%2BfTZptHfKu7kQR5b34QJxAPAf8iTlVHgi4%3D\u0026reserved=0\"\u003eshinyapps.io\u003c/a\u003e account (free) needed to deploy to the web.\u003c/p\u003e393:T663,\u003cp\u003eIn toda"])</script><script>self.__next_f.push([1,"y’s world, businesses can only survive and remain competitive if they embrace and leverage core technologies like cloud, AI, and data science. These are critical to driving significant growth and innovation within organizations, and are essential for the future of business.\u003c/p\u003e\r\n\r\n\u003cp\u003eThe courses featured in this program provide you with the core foundational knowledge of all three core technologies, including their business value and impact they provide, their applications and use cases, and an understanding of how these technologies work. You will not only become familiar with the common terms and tools associated with cloud, AI, and data science, but also experience them in action and learn hands-on skills to start working with them.\u003c/p\u003e\r\n\r\n\u003cp\u003eEach course includes hands-on assignments and interactions that demonstrate specific technologies in action. These practical exercises are suitable for even those without any specialized IT skills or programming knowledge. In fact, there is no prerequisite knowledge required to be successful in this program other than basic computer literacy skills and experiences with devices that support modern web browsers.\u003c/p\u003e\r\n\r\n\u003cp\u003eAlmost any organization that looks to disrupt or pioneer in a global or local market, and any individual looking to contribute to this vision needs to understand and leverage these essential technologies. What’s more, having skills and understanding in all three together will further increase your competitiveness and value in your company and the job market at large, and ultimately help you and your company reach your full potential.\u003c/p\u003e394:T8f7,"])</script><script>self.__next_f.push([1,"\u003cp\u003eIt is hard to overstate the importance of UX in our relationship with the digital environment. Forrester has established that organizations that invest in UX have fared better than most in bull markets and in recessions (Forrester, 2015). This is truer than ever, now that the pandemic has broadened the adoption of remote work, online social life and entertainment.\u003c/p\u003e\r\n \r\n\u003cp\u003eLearn User Experience fundamentals from the professors of the most important UX lab in North America. In this UX MicroMasters program, you will learn to meet organizational goals and satisfy users by applying a user-centred process to the digital products and services development that solve industry-relevant, real-world problems.\u003c/p\u003e\r\n\r\n\u003cp\u003eFor each user-centred development phase (UX Research, Design, Prototyping and Evaluation), you will acquire the relevant theoretical knowledge and the applied best practices to plan, perform, analyze and communicate useful insights for the following development phase.\u003c/p\u003e\r\n \r\n\u003cp\u003eFrom personal financial services and employee-oriented software to disruptive medical applications, this MicroMasters program will help you develop the design thinking, UX evaluation and UX project management skills necessary to generate new solutions to pressing problems.\u003c/p\u003e\r\n\r\n\u003cp\u003eIn each course, you will face a series of week-long challenges based on state-of-the-art research currently underway at HEC Montréal’s Tech3lab Laboratory. Through these challenges, you will refine your understanding of core concepts and prove your abilities in the very sought-after field of UX , from user interface, heuristic evaluation, human-computer interaction, usability testing, user interaction, to user experience.\u003c/p\u003e\r\n\r\n\u003cp\u003eThis rigorous graduate-level series represents 20% of the coursework towards a Master of Science degree in UX in a Business Context from HEC Montréal. You will have unique access to the Tech3lab, an applied laboratory in management science, specializing in the analysis of interactions between technological interfaces in organizations and their employees or customers.\u003c/p\u003e\r\n\r\n\u003chtml\u003e\r\n\u003cbody\u003e\r\n\r\n\u003cimg src=\"https://images.ctfassets.net/ii9ehdcj88bc/3kcIO09KMO9V3pLcmSgu5Z/89b3cdc9508a500d358329034d57268d/edxprize2022.png?h=250\" alt=\"edX Prize 2022\" \r\n\r\n\u003c/body\u003e\r\n\u003c/html\u003e"])</script><script>self.__next_f.push([1,"395:T57e,\u003cp\u003eThe first of the two courses will introduce systems of equations, which live at the heart of linear algebra. In this course you will explore fundamental concepts by exploring definitions and theorems that give a basis for this subject. You will apply an algorithm for solving linear systems that will be used for computations and for gaining insight into the properties of linear systems. This insight will all you to reduce problems involving linear combinations of vectors to approaches that involve systems of linear equations. You will also explore linear independence and linear transformations. They have an essential role throughout applications of linear algebra in many areas of industry, science, and engineering.\u003c/p\u003e\r\n\r\n\u003cp\u003eIn the second of these two courses you will see how we can apply the Invertible Matrix Theorem to describe how a square matrix might be used to solve linear equations. This theorem is a fundamental role in linear algebra, as it synthesizes many of the concepts introduced in the first course into one succinct concept. You will then explore theorems and algorithms that will allow you to apply linear algebra in ways that involve two or more matrices. You will examine partitioned matrices and matrix factorizations, which appear in most modern uses of linear algebra. You will also explore two applications of matrix algebra, to economics and to computer graphics.\u003c/p\u003e396:T935,"])</script><script>self.__next_f.push([1,"\u003cp\u003eThis certificate program consists of two mini-courses: (1) A Gentle Introduction to Probability; and (2) Random Variables – Great Expectations to Bell Curves.\u003c/p\u003e\r\n\r\n\u003cp\u003eThe first course provides an introduction to basic probability concepts. Our emphasis is on applications in science and engineering, with the goal of enhancing modeling and analysis skills for a variety of real-world problems.\u003c/p\u003e \r\n\r\n\u003cp\u003eIn order to make the course completely self-contained (and to bring back long-lost memories), we’ll start off with Bootcamp lessons to review concepts from set theory and calculus. We’ll then discuss the probability axioms that serve as the basis for all of our subsequent work – what makes probability tick?\u003c/p\u003e \r\n\r\n\u003cp\u003eThe next venues on our tour are the concepts of independence and conditional probability, which allow us to see how the probabilities of different events are related to each other, and how new information can be used to update probabilities. The course culminates in a discussion of Bayes Rule and its various interesting consequences related to probability updates.\u003c/p\u003e\r\n\r\n\u003cp\u003eThe second course discusses properties and applications of random variables.\u003c/p\u003e \r\n\r\n\u003cp\u003eWe’ll begin by introducing the concepts of discrete and continuous random variables. For instance, how many customers are likely to arrive in the next hour (discrete)? What’s the probability that a lightbulb will last more than a year (continuous)?\u003c/p\u003e\r\n\r\n\u003cp\u003eWe’ll learn about various properties of random variables such as the expected value, variance, and moment generating function. This will lead us to a discussion of functions of random variables. Such functions have many uses, including some wonderful applications in computer simulations.\u003c/p\u003e\r\n\r\n\u003cp\u003eIf you enjoy random variables, then you’ll really love joint (two-dimensional) random variables. We’ll provide methodology to extract marginal (one-dimensional) and conditional information from these big boys. This work will enable us to study the important concepts of independence and correlation.\u003c/p\u003e\r\n\r\n\u003cp\u003eAlong the way, we’ll start working with the R statistical package to do some of our calculations and analysis.\u003c/p\u003e\r\n\r\n\u003cp\u003eBy the end of the course, you will have the technology to model and evaluate a variety of real-world systems in which randomness is present.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"397:T53f,\u003cp\u003eThis certificate program will take students through roughly seven weeks of MATH 1554, Linear Algebra, as taught in the School of Mathematics at The Georgia Institute of Technology.\u003c/p\u003e \r\n\r\n\u003cp\u003eIn the first course, you will explore the determinant, which yields two important results. First, you will be able to apply an invertibility criterion for a square matrix that plays a pivotal role in, for example, computer graphics and in other more advanced courses, such as multivariable calculus. The first course then moves on to eigenvalues and eigenvectors. The goal of this part of the course is to decompose the action of a linear transformation that may be visualized. The main applications described here are to discrete dynamical systems, including Markov chains. However, the basic concepts afforded by eigenvectors and eigenvalues are useful throughout industry, science, engineering and mathematics.\u003c/p\u003e\r\n\r\n\u003cp\u003eIn the second course you will explore methods to compute an approximate solution to an inconsistent system of equations that have no solutions. This has a central role in the understanding of current data science applications. The second course then turns to symmetric matrices. They arise often in applications of the singular value decomposition, which is another tool often found in data science and machine learning.\u003c/p\u003e398:T60f,\u003cp\u003eHumans have always sought to know their own future, be it the destiny of an empire or an individual's fate. Across cultures and history, we find people trying to find their place in the Universe by attempting to gaze into the future.\u003c/p\u003e\n\u003cp\u003eJoin us for this one-week, immersive learning experience as we explore “pre-scientific” prediction systems ranging from \u003ca href=\"https://www.youtube.com/watch?v=8NQhFrsOOjg\u0026list=PLltdM60MtzxNRBvbLF2P_6Nudvt3OzLQE\u0026index=3\"\u003eancient Chinese bone burning\u003c/a\u003e to the \u003ca href=\"https://www.youtube.com/watch?v=CYEynNATHzg\u0026index=1\u0026t=1s\u0026list=PLltdM60MtzxNRBvbLF2P_6Nudvt3OzLQE\"\u003eOracle of Delphi\u003c/a\u003e to \u003ca href=\"https://www.youtube.com/watch?v=0f27u"])</script><script>self.__next_f.push([1,"dZU9C8\"\u003emodern astrology\u003c/a\u003e and \u003ca href=\"https://www.youtube.com/watch?v=GfFXPeGvmbE\u0026feature=youtu.be\"\u003etarot\u003c/a\u003e, with practitioners and Harvard faculty leading the journey. We will examine the details of over a dozen prediction systems as well as theoretical frameworks connecting them.\u003c/p\u003e\n\u003cp\u003eThis module is a part of PredictionX, which examines our efforts to predict the future over all of recorded history. PredictionX courses will cover topics from omens and oracles in ancient civilizations, which this course discusses, to the evolution of the general approach to science most take today (which includes the course \u003ca href=\"https://www.edx.org/course/predictionx-john-snow-cholera-epidemic-harvardx-soc1-jsx\"\u003eJohn Snow and the Cholera Outbreak of 1854\u003c/a\u003e) as well as modern computer simulations and the role they play in predicting our futures today.\u003c/p\u003e399:T6ae,\u003cp\u003eLinear Algebra: Foundations to Frontiers (LAFF) is packed full of challenging, rewarding material that is essential for mathematicians, engineers, scientists, and anyone working with large datasets. Students appreciate our unique approach to teaching linear algebra because:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eIt's visual.\u003c/li\u003e\n\u003cli\u003eIt connects hand calculations, mathematical abstractions, and computer programming.\u003c/li\u003e\n\u003cli\u003eIt illustrates the development of mathematical theory.\u003c/li\u003e\n\u003cli\u003eIt's applicable.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eIn this course, you will learn all the standard topics that are taught in typical undergraduate linear algebra courses all over the world, but using our unique method, you'll also get more! LAFF was developed following the syllabus of an introductory linear algebra course at The University of Texas at Austin taught by Professor Robert van de Geijn, an expert on high performance linear algebra libraries. Through short videos, exercises, visualizations, and programming assignments, you will study Vector and Matrix Operations, Linear Transformations, Solving Systems of Equations, Vector Spaces, Linear Least-Squares, and Eigenvalues and Eigenvectors. In addition, you wi"])</script><script>self.__next_f.push([1,"ll get a glimpse of cutting edge research on the development of linear algebra libraries, which are used throughout computational science.\u003c/p\u003e\n\u003cp\u003eMATLAB licenses will be made available to the participants free of charge for the duration of the course. \u003c/p\u003e\n\u003cp\u003eTo see what former learners have to say about the course, read reviews on \u003ca href=\"https://www.coursetalk.com/providers/edx/courses/linear-algebra-foundations-to-frontiers-2?page=1\u0026sort=-created_at%23incourse-reviews\"\u003ecoursetalk\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eWe invite you to LAFF with us!\u003c/p\u003e39a:T782,\u003cp\u003eA strong foundation in mathematics is critical for success in all science and engineering disciplines. Whether you want to make a strong start to a master’s degree, prepare for more advanced courses, solidify your knowledge in a professional context or simply brush up on fundamentals, this course will get you up to speed.\u003c/p\u003e\n\u003cp\u003eIn many engineering master’s programs, you need to be familiar with linear algebra. This course will enable you to review the relevant topics.\u003c/p\u003e\n\u003cp\u003eThis course focuses on vectors (from both algebraic and geometric perspectives) and solving linear equations. It will help you refresh your knowledge, test your skills and review the relations between the many concepts in linear algebra.\u003c/p\u003e\n\u003cp\u003eThe linear algebra courses within this series will offer you an overview of this branch of mathematics common to most engineering bachelor’s programs. They provide enough depth to cover the linear algebra you need to succeed in your engineering master’s or profession in areas such as computer graphics, systems and control, machine learning, quantum computing and more.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThis is a review course\u003c/strong\u003e\u003cbr /\u003e\nThis self-contained course is modular, so you do not need to follow the entire course if you wish to focus on a particular aspect. As a review course you are expected to have previously studied or be familiar with most of the material. Hence the pace will be higher than in an introductory course.\u003c/p\u003e\n\u003cp\u003eThis format is ideal for refreshing y"])</script><script>self.__next_f.push([1,"our bachelor level mathematics and letting you practice as much as you want. Through the Grasple platform, you will have access to plenty of exercises and receive intelligent, personal and immediate feedback.\u003c/p\u003e\n\u003cp\u003eThis course is part of our series \u003cstrong\u003eMastering Mathematics for Engineers\u003c/strong\u003e , and together with the course Linear Algebra II part of the program \u003cstrong\u003eMastering Linear Algebra\u003c/strong\u003e.\u003c/p\u003e39b:T453,\u003cp\u003eAt the beginning of this course we introduce the determinant, which yields two important concepts that you will use in this course. First, you will be able to apply an invertibility criterion for a square matrix that plays a pivotal role in, for example, the understanding of eigenvalues. You will also use the determinant to measure the amount by which a linear transformation changes the area of a region. This idea plays a critical role in computer graphics and in other more advanced courses, such as multivariable calculus. \u003c/p\u003e\n\u003cp\u003eThis course then moves on to eigenvalues and eigenvectors. The goal of this part of the course is to decompose the action of a linear transformation that may be visualized. The main applications described here are to discrete dynamical systems, including Markov chains. However, the basic concepts— eigenvectors and eigenvalues—are useful throughout industry, science, engineering and mathematics. \u003c/p\u003e\n\u003cp\u003eProspective students enrolling in this class are encouraged to first complete the linear equations and matrix algebra courses before starting this class.\u003c/p\u003e39c:T486,\u003cp\u003eUpon completion of this course, learners will be able to:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eCompute determinants of using cofactor expansions and properties of determinants\u003c/li\u003e\n\u003cli\u003eCompute the area of regions in R^3 under a given linear transformation using determinants\u003c/li\u003e\n\u003cli\u003eModel and solve real-world problems using Markov chains\u003c/li\u003e\n\u003cli\u003eVerify that a given vector is an eigenvector of a matrix\u003c/li\u003e\n\u003cli\u003eVerify that a scalar is an eigenvalue of a matrix\u003c/li\u003e\n\u003cli\u003eConstruct an eigenspace for a matrix\u003c/li\u003e\n\u003cli\u003eCharac"])</script><script>self.__next_f.push([1,"terize the invertibility of a matrix using determinants and eigenvalues\u003c/li\u003e\n\u003cli\u003eApply theorems related to eigenvalues (for example, to characterize the invertibility of a matrix)\u003c/li\u003e\n\u003cli\u003eFactorize 2 × 2 matrices that have complex eigenvalues\u003c/li\u003e\n\u003cli\u003eUse eigenvalues to determine identify the rotation and dilation of a linear transform\u003c/li\u003e\n\u003cli\u003eApply theorems to characterize matrices with complex eigenvalues\u003c/li\u003e\n\u003cli\u003eApply matrix powers and theorems to characterize the long-term behavior of a Markov chain\u003c/li\u003e\n\u003cli\u003eConstruct a transition matrix, a Markov Chain, and a Google Matrix for a given web, and compute the PageRank of the web.\u003c/li\u003e\n\u003c/ul\u003e39d:T70c,\u003cp\u003eA strong foundation in mathematics is critical for success in all science and engineering disciplines. Whether you want to make a strong start to a master’s degree, prepare for more advanced courses, solidify your knowledge in a professional context or simply brush up on fundamentals, this course will get you up to speed.\u003c/p\u003e\n\u003cp\u003eIn many engineering master’s programs, you need to be familiar with linear algebra. This course will enable you to review the relevant topics.\u003c/p\u003e\n\u003cp\u003eThis course focuses on matrices and linear transformations. Topics covered include matrix algebra, determinants, eigenvalues and eigenvectors, diagonalization and singular value decomposition. The course will help you refresh your knowledge, test your skills and review the relations between the many concepts in linear algebra.\u003c/p\u003e\n\u003cp\u003eThe linear algebra courses within this series will offer you an overview of this branch of mathematics common to most engineering bachelor’s programs. They provide enough depth to cover the linear algebra you need to succeed in your engineering master’s/profession in areas such as computer graphics, systems and control, machine learning, quantum computing and more.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThis is a review course\u003c/strong\u003e\u003cbr /\u003e\nThis self-contained course is modular, so you do not need to follow the entire course if you wish to focus on a particular aspect. As a "])</script><script>self.__next_f.push([1,"review course you are expected to have previously studied or be familiar with most of the material. Hence the pace will be higher than in an introductory course.\u003c/p\u003e\n\u003cp\u003eThis format is ideal for refreshing your bachelor level mathematics and letting you practice as much as you want. Through the Grasple platform, you will have access to plenty of exercises and receive intelligent, personal and immediate feedback.\u003c/p\u003e39e:Ta58,"])</script><script>self.__next_f.push([1,"\u003cp\u003eGain a good understanding of what Deep Learning is, what types of problems it resolves, and what are the fundamental concepts and methods it entails. The course developed by IVADO, Mila and Université de Montréal offers diversified learning tools for you to fully grasp the extent of this ground-breaking cross-cutting technology, a critical need in the field.\u003ca href=\"http://www.ivado.ca/en\"\u003e\u003c/a\u003e\u003c/p\u003e\n\u003cp\u003eIVADO, a scientific and economic data science hub bridging industrial, academic and government partners with expertise in digital intelligence designed the course, and the world-renowned \u003ca href=\"https://mila.quebec/en/\"\u003eMila\u003c/a\u003e, rallying researchers specialized in Deep Learning, created the content.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThis course is based on presentations from an event held in Montreal, from September 9 to 13, 2019. It was adapted to an online course (MOOC) format and was released, for the first time, in March 2020. The tutorials' material was updated on Colab Notebook in Spring of 2021.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMila’s founder and IVADO’s scientific director, \u003cstrong\u003e\u003ca href=\"https://mila.quebec/en/yoshua-bengio/\"\u003eYoshua Bengio\u003c/a\u003e, also a professor at Université de Montréal, is a world-leading expert in artificial intelligence and a pioneer in deep learning as well as the scientific director of this course\u003c/strong\u003e. He is also a joint recipient of the 2018 A.M. Turing Award, “the Nobel Prize of Computing”, for conceptual and engineering breakthroughs that have made deep neural networks a critical component of computing.\u003c/p\u003e\n\u003cp\u003eDeep Learning is an extension of Machine Learning where machines can learn by experience without human intervention. It is largely influenced by the human brain in the fact that algorithms, or artificial neural networks, are able to learn from massive amounts of data and acquire skills that a human brain would. Thus, Deep learning is now able to tackle a large variety of tasks that were considered out of reach a few years ago in computer vision, signal processing, natural language processing, robotics, and sequential decision-making. Because of these recent advances, various industries are now deploying deep learning models that impact various economic sectors such as transport, health, finance, energy, as well as our daily life in general.\u003c/p\u003e\n\u003cp\u003eIf you are a professional, a scientist or an academic with basic knowledge in mathematics and programming, this MOOC is designed for you! Atop the rich Deep Learning content, discover issues of bias and discrimination in machine learning and benefit from this sociotechnical topic that has proven to be a great eye-opener for many.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"39f:T930,"])</script><script>self.__next_f.push([1,"\u003cp\u003eSpeech recognition, drones, and self-driving cars – things that once seemed like pure science fiction – are now widely available technologies, and just a few examples of how humans have taught machines to analyze data and make decisions. In this hands-on, introductory course, you will examine all the forms in which data exists, learn tools that uncover relationships between data, and leverage basic algorithms to understand the world from a new perspective.\u003c/p\u003e\n\u003cp\u003eWhether you're a high school student or someone switching careers, all you need to get started in this course is a curiosity about the topic of machine learning and a willingness to tinker around with your computer.\u003c/p\u003e\n\u003cp\u003eThe course is taught by modules. Within each module, you'll have access to videos, short exercises, and a final capstone project. In Module 1, you'll begin by looking at different kinds of data. To help you explore the data, you'll dive right into some programming with the Python programming language. You don't need to have any programming background, we will guide you on how to leverage Python to explore and visualize any data.\u003c/p\u003e\n\u003cp\u003eOne kind of data you'll work with is data that relates one variable to another. Coming up with a relationship between two variables—one depending on the other—is at the center of Module 2. In that module, you'll build up some core concepts before seeing your first machine learning algorithm. The goal is to use programming to create models that describe mathematical relationships between data. You'll be able to see how good the model is and use it to make predictions about new data.\u003c/p\u003e\n\u003cp\u003eIn Module 3, you'll see a discussion about where imperfections in collected data might come from. You rarely have perfectly “clean” data sets, so it's important to understand how imperfections impact the model that an algorithm might come up with. To this end, we will introduce the notion of data distributions and build up to the concepts of biased and unbiased noise.\u003c/p\u003e\n\u003cp\u003eAnother kind of data you'll work with is data that belongs in different groups (or classes). Creating a model that predicts what group data belongs in is at the center of Module 4. You'll work through different ways of thinking about this problem and see three different ways of approaching making such groupings (classification).\u003c/p\u003e"])</script><script>self.__next_f.push([1,"3a0:T5bc,\u003cp\u003eThis module is currently offered in the Lyles School of Civil Engineering as part of the CE57200 “Prestressed Concrete Design” 3-Credits (CR) course in the area of structural engineering available to senior undergraduate/graduate students. It integrates science and engineering principles to design prestressed concrete members and structural systems. The application of scientific and engineering knowledge is demonstrated in solving engineering problems associated with the design of precast prestressed building members both composite and non-composite for superimposed loads, and one-way post-tensioned floor slabs systems bonded and unbonded also composite and non-composite for superimposed loads. Design of pretensioned Hollow-Core slabs, Double-Tee and I-Beam members, and one-way post-tensioned floor slabs is exercised using current building code requirements to provide experiences in realistic design practice. The following subjects are used to solve engineering problems: calculus and differential equations; use of computer tools, data manipulation, statistical analysis, numerical calculation, and reinforced concrete design principles.\u003c/p\u003e\n\u003cp\u003eThe course is developed in three modules each of 1-CR. Module 2 (this module) is focused on the essentials of design of pretensioned concrete structures.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThis course is available to practicing engineers for 1.5 CEUs for learners completing the course on the verified track.\u003c/strong\u003e\u003c/p\u003e3a1:T5be,\u003cp\u003eThis module is currently offered in the Lyles School of Civil Engineering as part of the CE57200 “Prestressed Concrete Design” 3-Credits (CR) course in the area of structural engineering available to senior undergraduate/graduate students. It integrates science and engineering principles to design prestressed concrete members and structural systems. The application of scientific and engineering knowledge is demonstrated in solving engineering problems associated with the design of precast prestressed building members both composite and non-composite"])</script><script>self.__next_f.push([1," for superimposed loads, and one-way post-tensioned floor slabs systems bonded and unbonded also composite and non-composite for superimposed loads. Design of pretensioned Hollow-Core slabs, Double-Tee and I-Beam members, and one-way post-tensioned floor slabs is exercised using current building code requirements to provide experiences in realistic design practice. The following subjects are used to solve engineering problems: calculus and differential equations; use of computer tools, data manipulation, statistical analysis, numerical calculation, and reinforced concrete design principles.\u003c/p\u003e\n\u003cp\u003eThe course is developed in three modules each of 1-CR. Module 3 (this module) is focused on the essentials of design of post-tensioned concrete structures.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThis course is available to practicing engineers for 1.5 CEUs for learners completing the course on the verified track.\u003c/strong\u003e\u003c/p\u003e3a2:T5fe,\u003cp\u003eThis module is currently offered in the Lyles School of Civil Engineering as part of the CE57200 “Prestressed Concrete Design” 3-Credits (CR) course in the area of structural engineering available to senior undergraduate/graduate students. It integrates science and engineering principles to design prestressed concrete members and structural systems. The application of scientific and engineering knowledge is demonstrated in solving engineering problems associated with the design of precast prestressed building members both composite and non-composite for superimposed loads, and one-way post-tensioned floor slabs systems bonded and unbonded also composite and non-composite for superimposed loads. Design of pretensioned Hollow-Core slabs, Double-Tee and I-Beam members, and one-way post-tensioned floor slabs is exercised using current building code requirements to provide experiences in realistic design practice. The following subjects are used to solve engineering problems: calculus and differential equations; use of computer tools, data manipulation, statistical analysis, numerical calculation, and reinforced"])</script><script>self.__next_f.push([1," concrete design principles.\u003c/p\u003e\n\u003cp\u003eIn the edX platform, the course is developed in three modules each of 1-credit. \u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eFundamentals of Prestressed Concrete (this course)\u003c/li\u003e\n\u003cli\u003ePretensioned Structures\u003c/li\u003e\n\u003cli\u003ePost-Tensioned Structures\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eThis course is available to practicing engineers for 1.5 CEUs for learners completing the course on the verified track.\u003c/strong\u003e\u003c/p\u003e3a3:T489,\u003cp\u003eWe think of Robotics as the science of building devices that physically interact with their environment. The most useful robots do it precisely, powerfully, repeatedly, tirelessly, fast, or some combinations of these. The most interesting robots maybe even do it intelligently. This course will cover the fundamentals of robotics, focusing on both the mind and the body.\u003c/p\u003e\n\u003cp\u003eWe will learn about two core robot classes: kinematic chains (robot arms) and mobile bases. For both robot types, we will introduce methods to reason about 3-dimensional space and relationships between coordinate frames. For robot arms, we will use these to model the task of delivering a payload to a specified location. For mobile robots, we will introduce concepts for autonomous navigation in the presence of obstacles.\u003c/p\u003e\n\u003cp\u003eClass projects will make use of ROS - the open-source Robot Operating System (\u003ca href=\"http://www.ros.org\"\u003ewww.ros.org\u003c/a\u003e) widely used in both research and industry. Computer requirements for working on the projects will include a computer set up with Ubuntu Linux and high bandwidth internet access for downloading and installing ROS packages.\u003c/p\u003e3a4:Tb76,"])</script><script>self.__next_f.push([1,"\u003cp\u003eStudents are welcome to participate in the study of \"Introduction to Modern Biology\". In this semester, we will learn basic and cutting-edge knowledge related to life. This course first explains the basic theories of biology according to a layer-by-layer framework: at the molecular and cellular level, we will learn about cell structure, growth, division, and cell communication; at the individual level, we will learn about heredity and development Principle; at the population level, you will understand biological evolution, that is, the gradual change of the entire population between generations, which ultimately led to the variety of organisms we see today through natural selection; at the level of biological communities and ecosystems, you will learn about ecology Science, the study of how organisms interact with each other and with their environment. This course will also specifically explore the products of evolution---organisms, focusing on their structure and function, which is the most interesting and important part for most students. Biology is a rapidly developing discipline, which is not only reflected in the discovery and understanding of more and more biological phenomena, but also in the application of new biological technologies and the intersection of disciplines. Therefore, this course pays special attention to understanding the latest advances in modern biology including gene therapy, stem cell research, recombinant DNA, biochips and other frontiers. Moreover, the cross-application of biology with physics, chemistry, mathematics, computers, psychology and other disciplines will be discussed. Biology is also an experimental science. We will introduce some classic, interesting, and even controversial biological experiments and their designs. We hope that students can develop critical thinking while learning. The classroom teaching of this course pursues easy-to-understand, close connection between macro and micro, and combination of basics and applications to help students deepen their understanding of the basic concepts and principles of life sciences and guide students to establish a correct scientific attitude. This introductory course includes the fundamental principles of biochemistry, genetics, molecular biology, and cell biology. Biological function at the molecular level is particularly emphasized and covers the structure and regulation of genes, as well as, the structure and synthesis of proteins, how these molecules are integrated into cells, and how these cells are integrated into multicellular systems and organisms. In addition, each version of the subject has its own distinctive material. All these knowledge are applied to more advanced subjects, like immunology, neurobiology, endocrinology and human behavior. This course also focuses on the exploration of current research in cell biology, immunology, neurobiology, genomics, and molecular medicine.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"3a5:T456,\u003cp\u003eIn this course, part of our \u003ca href=\"https://www.edx.org/professional-certificate/harvardx-data-science\"\u003eProfessional Certificate Program in Data Science\u003c/a\u003e,you will learn valuable concepts in probability theory. The motivation for this course is the circumstances surrounding the financial crisis of 2007-2008. Part of what caused this financial crisis was that the risk of some securities sold by financial institutions was underestimated. To begin to understand this very complicated event, we need to understand the basics of probability. \u003c/p\u003e\n\u003cp\u003eWe will introduce important concepts such as random variables, independence, Monte Carlo simulations, expected values, standard errors, and the Central Limit Theorem. These statistical concepts are fundamental to conducting statistical tests on data and understanding whether the data you are analyzing is likely occurring due to an experimental method or to chance. \u003c/p\u003e\n\u003cp\u003eProbability theory is the mathematical foundation of statistical inference which is indispensable for analyzing data affected by chance, and thus essential for data scientists.\u003c/p\u003e3a6:T9f1,"])</script><script>self.__next_f.push([1,"\u003cp\u003eEveryone has an opinion on parenting – where babies should sleep, what they should eat, and whether parents should spank, scold, or praise. What’s more, the media often offers support for whichever opinions appear most popular at any given time. This leavesthose of us who like to base our decisions on firm, provablefacts feeling dizzy. \u003c/p\u003e\n\u003cp\u003e“The Science of Parenting” addresses this confusion by moving beyond the chatter and opinion surrounding parenting, and by \u003cstrong\u003elooking directly at the science\u003c/strong\u003e. Parenting itself is far from a science. Nevertheless, scientists have conducted thousands of studies that can help parents – or future parents – make sensible, informed decisions. \u003c/p\u003e\n\u003cp\u003eOne goal of this coursewill be to provide a \u003cstrong\u003esurvey of important scientific findings\u003c/strong\u003e spanning a range of topics that are central to the lives of parents: \u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003ediet\u003c/li\u003e\n\u003cli\u003esleep\u003c/li\u003e\n\u003cli\u003ediscipline\u003c/li\u003e\n\u003cli\u003elearning\u003c/li\u003e\n\u003cli\u003escreen time\u003c/li\u003e\n\u003cli\u003eimpulse control\u003c/li\u003e\n\u003cli\u003evaccination\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eWe’ll also \u003cstrong\u003eexplore ongoing mysteries\u003c/strong\u003e , like what causes autism, and why so many children are allergic to peanuts. \u003c/p\u003e\n\u003cp\u003ePerhaps more important, this coursewill not only dig into existing science, but will also \u003cstrong\u003eexplore the underlying nature of parenting science itself\u003c/strong\u003e. Often, scientists measure correlations: They ask how different parenting practices are related to different behaviors in children. But the claims they make from 'correlational data are often much, much stronger. For example, from correlational data, scientists often claim that parents cause the behaviors of their kids. This coursewill show how this type of error – common in the scientific literature – can \u003cstrong\u003eexplain a significant amount of the confusion present in the media\u003c/strong\u003e and general public. Wewill discuss how to avoid the same error when evaluating science, and how to use the sum of available evidence to inform decision making. \u003c/p\u003e\n\u003cp\u003eThe course’s instructor, David Barner, is a leading authority on cognitive development. He is joined by leading experts on behavior genetics, vaccination, autism, lying, and spanking, as well as by real live parents who try to use science to inform their decisions. This class is suitable not only for parents, future parents, and grandparents, but also for \u003cstrong\u003eprofessionals interested in health care, social work, and early childhood education\u003c/strong\u003e who want to increase their knowledge and analysis skills.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"3a7:T5e8,\u003cp\u003eMathematics is the most essential tool in any STEM professional’s toolbox. In this course, we will provide you with an introduction to linear algebra, multivariable calculus, and differential equations, through exploring the main definitions, theorems and practical examples required. \u003c/p\u003e\n\u003cp\u003eCan we use linear algebra to do data compression? What’s the meaning of an eigenvalue and an eigenvector in a mechanical system? How do vector fields help to describe wind flow? How can you make optimal parameter choices in industrial processes?\u003c/p\u003e\n\u003cp\u003eWe aim to answer all these questions and more, so that you can use these mathematical techniques when tackling problems in your own field of study.\u003c/p\u003e\n\u003cp\u003eWe will use examples, graphic representations, applets, and exercises to exemplify the various theorems and definitions.\u003c/p\u003e\n\u003cp\u003eYou will acquire the skills to cope with matrix-formulated problems typically arising from applications in science and technology. Not only will you be able to use practical algorithms, solve systems of equations and differential equations, compute the singular value and eigenvalue decomposition, and solve optimisation problems, you will also acquire a set of properties that will assist in simplifying and understanding mathematical problems.\u003c/p\u003e\n\u003cp\u003eThe course will give you the tools to transform optimisation problems and differential equations into matrix language. Most importantly, you will learn that matrix computations are ubiquitous in science and engineering.\u003c/p\u003e3a8:T48d,\u003cul\u003e\n\u003cli\u003eWhat vector spaces are and how their elements can be represented by coordinate vectors with respect to a basis\u003c/li\u003e\n\u003cli\u003eLinear transformations between vector spaces and how to represent them in matrix notation\u003c/li\u003e\n\u003cli\u003eTo compute inner products, norms, and orthogonal projections\u003c/li\u003e\n\u003cli\u003eTo define and calculate eigenvalues and eigenvectors and their algebraic and geometric multiplicities\u003c/li\u003e\n\u003cli\u003eTo calculate the singular value decomposition\u003c/li\u003e\n\u003cli\u003eTo understand the concepts of a real function of multi"])</script><script>self.__next_f.push([1,"ple variables, partial and directional derivatives and the multivariate chain rule\u003c/li\u003e\n\u003cli\u003eTo determine critical points and identify extrema of multivariate functions\u003c/li\u003e\n\u003cli\u003eTo understand the concepts of (conservative) vector fields and be able to calculate and simplify their line integrals\u003c/li\u003e\n\u003cli\u003eTo understand what gradient, divergence, and curl operators are and how to calculate them\u003c/li\u003e\n\u003cli\u003eTo classify and solve (systems of) first-order differential equations\u003c/li\u003e\n\u003cli\u003eTo understand and apply linear algebra techniques to solve linear systems of differential equations with constant coefficients and analyse their stability\u003c/li\u003e\n\u003c/ul\u003e3a9:T694,\u003cp\u003eEvery single minute, computers across the world collect millions of gigabytes of data. What can you do to make sense of this mountain of data? How do data scientists use this data for the applications that power our modern world?\u003c/p\u003e\n\u003cp\u003eData science is an ever-evolving field, using algorithms and scientific methods to parse complex data sets. Data scientists use a range of programming languages, such as Python and R, to harness and analyze data. This course focuses on using Python in data science. By the end of the course, you’ll have a fundamental understanding of machine learning models and basic concepts around Machine Learning (ML) and Artificial Intelligence (AI).\u003c/p\u003e\n\u003cp\u003eUsing Python, learners will study regression models (Linear, Multilinear, and Polynomial) and classification models (kNN, Logistic), utilizing popular libraries such as sklearn, Pandas, matplotlib, and numPy. The course will cover key concepts of machine learning such as: picking the right complexity, preventing overfitting, regularization, assessing uncertainty, weighing trade-offs, and model evaluation. Participation in this course will build your confidence in using Python, preparing you for more advanced study in Machine Learning (ML) and Artificial Intelligence (AI), and advancement in your career.\u003c/p\u003e\n\u003cp\u003eLearners must have a minimum baseline of programming knowledge (preferably in Python"])</script><script>self.__next_f.push([1,") and statistics in order to be successful in this course. Python prerequisites can be met with an introductory Python course offered through CS50’s Introduction to Programming with Python, and statistics prerequisites can be met via Fat Chance or with Stat110 offered through HarvardX.\u003c/p\u003e3aa:Tf4f,"])</script><script>self.__next_f.push([1,"\u003cp\u003e\u003cstrong\u003e\u003cem\u003e*\u003c/em\u003e\u003c/strong\u003e \u003cem\u003e\u003cspan lang=\"EN-US\"\u003e\u003cstrong\u003eGOLD Award Winner of QS Reimagine Education Award 2021 in Life Sciences!\u003c/strong\u003e\u003c/span\u003e\u003c/em\u003e *\u003c/p\u003e\n\u003cp\u003eThis course, developed by the Department of Diagnostic Radiology, The University of Hong Kong in collaboration with committee members of international and national cardiac imaging societies, is for radiologists, cardiologists, radiographers/ technologists and other health professionals who want to learn more about this imaging modality. 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Previous experience in cardiac CT is not required.\u003c/p\u003e\n\u003cp\u003eLearning outcomes:\u003c/p\u003e\n\u003col\u003e\n\u003cli\u003eUnderstanding of the common cardiac CT examinations in order to better understand how to acquire cardiac images and to interpret them.\u003c/li\u003e\n\u003cli\u003eAbility to analyse cardiac CT images at level 1 competency such as calcium score, CT coronary angiography, TAVI.\u003c/li\u003e\n\u003cli\u003eAttain hands-on experience to analyse real cases from a database of 50 clinical cases, using dedicated software, as well as further supplementation through our web forum.\u003c/li\u003e\n\u003cli\u003eBasic understanding of future developments in the cardiac CT field.\u003c/li\u003e\n\u003cli\u003eProvide career advice and thoughts from well-known experts through exclusive interviews.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eA MOOC on cardiovascular magnetic resonance will be available on this platform in the near future. Watch this space!\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgments\u003c/em\u003e\u003cbr /\u003e\n\u003c/strong\u003e This course is supported by the grant from Sanming Project of Medicine in Shenzhen. We would like to thank Miss Benedicte Coiffier and Miss Bohan Fan from the Department of Diagnostic Radiology, The University of Hong Kong (HKU), for coordinating the online courses and the HKU Technology-Enriched Learning Initiative (TELI) team for producing the educational material. We would like to express our sincere thanks to our colleagues Luo Lin, Chen Yan, and Baroc Ho from the Radiology Division, Department of Medical Imaging, The University of Hong Kong-Shenzhen Hospital, for translating all the texts into Chinese and Dr Nitin Ramamurthy and Dr Jhonatan Bringas for their additional help.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e*入圍2020年QS全球教育創新大獎之電子學習類別！\u003c/em\u003e\u003c/strong\u003e *\u003c/p\u003e\n\u003cp\u003e本课程由香港大学放射诊断科与国内外心脏影像学会的委员会成员合作开发，专为想进一步了解心脏成像技术的放射科医师、心内科及心外科医师、放射技师、工程师和其他医疗健康专业人士而设计。本课程根据心脏成像协会一级建议，涵盖了所需的主题，并提供50个心脏CT真实病例。学习者不要求有心脏CT的过往经验。\u003c/p\u003e\n\u003cp\u003e学习成果：\u003c/p\u003e\n\u003col\u003e\n\u003cli\u003e了解常见的心脏CT检查，以便更好地掌握如何获取心脏图像并解释它们。\u003c/li\u003e\n\u003cli\u003e具备心脏CT图像的一级分析能力，如能够进行钙化评分，分析CT冠状动脉造影，TAVI等。\u003c/li\u003e\n\u003cli\u003e从临床病例数据库中获取50个真实病例，利用专业后处理软件及平台论坛提供的材料进行教学操作以获得实践经验。\u003c/li\u003e\n\u003cli\u003e对心脏CT领域未来发展的有基本认识。\u003c/li\u003e\n\u003cli\u003e通过独家采访，了解知名专家对学生的职业建议和想法。\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e未来将会在这个平台上发布一个关于心血管磁共振（CMR）的课程。请留意关注!\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e致謝\u003c/em\u003e\u003cbr /\u003e\n\u003c/strong\u003e 此课程获得深圳医疗卫生“三名工程”的资助。我们衷心感谢香港大学放射诊断科的Benedicte Coiffier和范博涵协助组织在线课程，以及香港大学科创习新小组制作课程材料。我们非常感谢香港大学深圳医院医学影像中心放射科的同事罗琳、陈燕与何健龙把所有文本翻译成中文。感谢Dr Nitin Ramamurthy 和Dr Jhonatan Bringas的帮助。\u003c/p\u003e"])</script><script>self.__next_f.push([1,"3ab:T5e5,\u003cp\u003eThis physics course covers the physical principles of major in vivo bio-imaging modalities and the different imaging techniques.\u003c/p\u003e\n\u003cp\u003eAfter a short study of ultrasound imaging, you will learn about the different X-ray imaging techniques. The understanding of the interaction of X-rays with tissue will lead to the study of three different techniques:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eComputed Tomography (CT)\u003c/li\u003e\n\u003cli\u003eEmission Tomography\u003c/li\u003e\n\u003cli\u003ePositron Emission Tomography (PET)\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThis course shows how existing physical principles transcend into bio-imaging and establish an important link into life sciences, illustrating the contributions physics can make to life sciences. Practical examples will be shown to illustrate the respective imaging modality, its use, premise and limitations, and biological safety will be touched upon.\u003c/p\u003e\n\u003cp\u003eDuring this course, you will develop a good understanding of the mechanisms leading to tissue contrast of the bio-imaging modalities covered in this course, including the inner workings of the scanner and how they define the range of possible biomedical applications. You will be able to judge which imaging modality is adequate for specific life science needs and to understand the limits and promises of each modality.\u003c/p\u003e\n\u003cp\u003eTo learn more about biomedical imaging, join us in the second part of this course \u003ca href=\"https://www.edx.org/course/fundamentals-biomedical-imaging-magnetic-epflx-fndbioimg2x\"\u003eBiomedical Imaging: Magnetic Resonance Imaging (MRI)\u003c/a\u003e.\u003c/p\u003e3ac:Tb4d,"])</script><script>self.__next_f.push([1,"\u003cp\u003eThis course teaches the R programming language in the context of statistical data and statistical analysis in the life sciences.\u003c/p\u003e\n\u003cp\u003eWe will learn the basics of statistical inference in order to understand and compute p-values and confidence intervals, all while analyzing data with R code. We provide R programming examples in a way that will help make the connection between concepts and implementation. Problem sets requiring R programming will be used to test understanding and ability to implement basic data analyses. We will use visualization techniques to explore new data sets and determine the most appropriate approach. We will describe robust statistical techniques as alternatives when data do not fit assumptions required by the standard approaches. By using R scripts to analyze data, you will learn the basics of conducting reproducible research.\u003c/p\u003e\n\u003cp\u003eGiven the diversity in educational background of our students we have divided the course materials into seven parts. You can take the entire series or individual courses that interest you. If you are a statistician you should consider skipping the first two or three courses, similarly, if you are biologists you should consider skipping some of the introductory biology lectures. Note that the statistics and programming aspects of the class ramp up in difficulty relatively quickly across the first three courses. We start with simple calculations and descriptive statistics. By the third course will be teaching advanced statistical concepts such as hierarchical models and by the fourth advanced software engineering skills, such as parallel computing and reproducible research concepts.\u003c/p\u003e\n\u003cp\u003eThese courses make up two Professional Certificates and are self-paced:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Analysis for Life Sciences:\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/statistics-and-r\"\u003ePH525.1x: Statistics and R for the Life Sciences\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/introduction-to-linear-models-and-matrix-algebra\"\u003ePH525.2x: Introduction to Linear Models and Matrix Algebra\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/statistical-inference-and-modeling-for-high-throug\"\u003ePH525.3x: Statistical Inference and Modeling for High-throughput Experiments\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/high-dimensional-data-analysis\"\u003ePH525.4x: High-Dimensional Data Analysis\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eGenomics Data Analysis:\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/introduction-to-bioconductor-annotation-and-analys\"\u003ePH525.5x: Introduction to Bioconductor\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/case-studies-in-functional-genomics\"\u003ePH525.6x: Case Studies in Functional Genomics\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.edx.org/course/advanced-bioconductor\"\u003ePH525.7x: Advanced Bioconductor\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThis class was supported in part by NIH grant R25GM114818.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"3ad:T4cc,\u003cp\u003eLinear algebra is at the core of all of modern mathematics, and is used everywhere from statistics and data science, to economics, physics and electrical engineering. However, learning the subject is not principally about acquiring computational ability, but is more a matter of fluency in its language and theory.\u003c/p\u003e\n\u003cp\u003eIn this course, we will start with systems of linear equations, and connect them to vectors and vector spaces, matrices, and linear transformations. We will be emphasizing the vocabulary throughout, so that students become comfortable working with the different aspects.\u003c/p\u003e\n\u003cp\u003eWe will then introduce matrix and vector operations such as matrix multiplication and inverses, paying particular attention to their underlying purposes. Students will learn not just how to calculate them, but also why they work the way that they do.\u003c/p\u003e\n\u003cp\u003eWe willdiscuss the key concepts of basis and dimension, which form the foundation for many of the more advanced concepts of linear algebra.\u003c/p\u003e\n\u003cp\u003eThe last chapter concerns inner products, which allow us to use linear algebra for approximating solutions; we will see how this allows for applications ranging from statistics and linear regression to digital audio.\u003c/p\u003e3ae:T403,\u003cp\u003eThis course will cover the theory and the fundamentals of the emerging science of Sabermetrics. We will discuss the game of baseball, not through consensus or a fan’s conventional wisdom, but by searching for objective knowledge in baseball performance. These and other areas of sabermetrics will be analyzed and better understood with current and historical baseball data. \u003c/p\u003e\n\u003cp\u003eThe course also serves as applied introduction to the basics of data science, an emerging field of scholarship, that requires skills in computation, statistics, and communicating results of analyses. Using baseball data, the basics of statistical regression, the R Language, and SQL will be covered.\u003c/p\u003e\n\u003cp\u003eThis course was successfully taught on the edX platform as a MOOC in 2014. This course has also been success"])</script><script>self.__next_f.push([1,"fully taught at the Experimental College at Tufts University since 2004. Many of its former students have gone on to careers writing about baseball and working in various MLB baseball operations and analytics departments.\u003c/p\u003e3af:T790,\u003cp\u003eA strong foundation in mathematics is critical for success in all science and engineering disciplines. Whether you want to make a strong start to a master’s degree, prepare for more advanced courses, solidify your knowledge in a professional context or simply brush up on fundamentals, this course will get you up to speed.\u003c/p\u003e\n\u003cp\u003eThis course allows you to get a solid basis by refreshing and reviewing your bachelor-level calculus.\u003c/p\u003e\n\u003cp\u003eThe course focuses on functions of one variable. In the first 5 weeks you will learn all the basic integration, differentiation and approximation techniques required in a first calculus course of an engineering bachelor education. In the final week these topics will all come together as you solve and analyze several ordinary differential equations.\u003c/p\u003e\n\u003cp\u003eWe use examples that are based on real-life applications so you can practice your mathematical skills in an engineering context. Our courses in calculus offer enough depth to cover what you need to succeed in your engineering master’s or profession in areas such as modeling, physics, fluid dynamics, dynamical systems and more.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThis is a review course\u003c/strong\u003e\u003cbr /\u003e\nThis self-contained course is modular, so you do not need to follow the entire course if you wish to focus on a particular aspect. As a review course you are expected to have previously studied or be familiar with most of the material. Hence the pace will be higher than in an introductory course.\u003c/p\u003e\n\u003cp\u003eThis format is ideal for refreshing your bachelor level mathematics and letting you practice as much as you want. Through the Grasple platform, you will have access to plenty of exercises and receive intelligent, personal and immediate feedback.\u003c/p\u003e\n\u003cp\u003eThis course is part of our series \u003cstrong\u003eMastering Mathematics for "])</script><script>self.__next_f.push([1,"Engineers\u003c/strong\u003e , and together with the course Calculus II part of the program \u003cstrong\u003eMastering Calculus\u003c/strong\u003e.\u003c/p\u003e3b0:T81b,"])</script><script>self.__next_f.push([1,"\u003cp\u003eModern IT infrastructure is built as distributed systems, an exciting concept that started with the first computers and evolved rapidly into its present form. From online video meetings to internet services, from social media platforms to online games, we all use and interact with distributed systems on a daily basis and increasingly depend on them. Designing and operating such large-scale distributed systems, however, is complex and typically involves making reasonable compromises. There are fundamental technical barriers as well as economic arguments why we cannot make these systems behave as if they were running on a single, perfectly reliable machine.. \u003c/p\u003e\n\u003cp\u003eIn this course, learners will be introduced to the essential functional and non-functional concerns of distributed systems and the common problems encountered while designing them, such as consistency, availability, elasticity, and scalability. A variety of practical solutions that have been established in the leading tech industry in recent years will be reviewed. These provide re-usable building blocks to create new large-scale applications. These recent developments, especially around cloud computing, large-scale data processing, distributed machine learning, and other fields are often not reflected in textbooks and are absent from many traditional curricula but are at the heart of this course. \u003c/p\u003e\n\u003cp\u003eThe course will therefore provide learners with the fundamental understanding (theoretical and practical foundations) of how cloud, edge, and big data processing systems work and how they address common challenges for distributed systems such as performance, resilience, and scalability.\u003c/p\u003e\n\u003cp\u003eThe learning progress is assessed through a variety of different activities including quizzes, design exercises, experiments, and open questions, with peer review of other students’ solutions. In the final project, learners will design a distributed system based on the learners’ own experience and interests and describe the functional and non-functional properties of the system.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"3b1:T5d6,\u003cp\u003eIs my code fast? Can it be faster? Scientific computing, machine learning, and data science are about solving problems that are compute intensive. Choosing the right algorithm, extracting parallelism at various levels, and amortizing the cost of data movement are vital to achieving scalable speedup and high performance. \u003c/p\u003e\n\u003cp\u003eIn this course, the simple but important example of matrix-matrix multiplication is used to illustrate fundamental techniques for attaining high-performance on modern CPUs. A carefully designed and scaffolded sequence of exercises leads the learner from a naive implementation to one that effectively utilizes instruction level parallelism and culminates in a high-performance multithreaded implementation. Along the way, it is discovered that careful attention to data movement is key to efficient computing. \u003c/p\u003e\n\u003cp\u003ePrerequisites for this course are a basic understanding of matrix computations (roughly equivalent toWeeks 1-5 of Linear Algebra: Foundations to Frontiers on edX) and an exposure to programming. Hands-on exercises start with skeletal code in the C programming language that is progressively modified, so that extensive experience with C is not required. 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For this purpose, we will take advantage of the availability of cloud-based access to quantum computers and quantum software.\u003c/p\u003e\n\u003cp\u003eThe material will appeal to engineering students, natural sciences students, and professionals whose interests are in using as well as developing quantum technologies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAttention:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eQuantum Computing 1: Fundamentals\u003c/em\u003e is an essential prerequisite to \u003cem\u003eQuantum Computing 2: Hardware\u003c/em\u003e and \u003cem\u003eQuantum Computing 3: Algorithm and Software\u003c/em\u003e. Learners should plan to complete Fundamentals (1) before enrolling in the Hardware (2) or the Algorithm and Software (3) courses.\u003c/p\u003e\n\u003cp\u003eAlternatively, learners can enroll in courses 2 or 3 if they have solid experience with or knowledge of quantum computing fundamentals, including the following: 1) postulates of quantum mechanics; 2) gate-based quantum computing; 3) quantum errors and error correction; 3) adiabatic quantum computing; and 5) quantum applications and NISQ-era.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"3b3:Tad7,"])</script><script>self.__next_f.push([1,"\u003cp\u003e\u003cem\u003e\u003cspan lang=\"EN-US\"\u003e\u003cstrong\u003e\u003cem\u003eGOLD Award Winner of QS Reimagine Education Award 2021 in Life Sciences!\u003c/em\u003e\u003c/strong\u003e\u003c/span\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis course is for radiologists, cardiologists, radiographers/ technologists and other health professionals who want to learn more about cardiovascular magnetic resonance imaging (CMR). Previous experience in CMR is not required.\u003c/p\u003e\n\u003cp\u003eThe learning outcomes are:\u003c/p\u003e\n\u003col\u003e\n\u003cli\u003eUnderstanding of the basic CMR physics and sequences in order to better understand how to acquire cardiac images and how to assess commonly used sequences (eg. Steady state free precession sequence, phase contrast to measure blood flow, T2* and magnetic resonance angiography).\u003c/li\u003e\n\u003cli\u003eUnderstand the safety profile and risks of contrast agents used in CMR.\u003c/li\u003e\n\u003cli\u003eAbility to analyse CMR images at SCMR level 1 competency such as stress perfusion, late gadolinium enhancement and post-processing for ventricular function.\u003c/li\u003e\n\u003cli\u003eAttain hands-on experience to analyse real clinical cases from a database of 50 clinical cases, using dedicated CMR software, as well as further supplementation through our web forum.\u003c/li\u003e\n\u003cli\u003eBasic understanding of future developments in the CMR field such as exercise CMR, artificial intelligence, feature tracking, T1 and T2 mapping.\u003c/li\u003e\n\u003cli\u003eProvide career advice and thoughts from well-known CMR experts through exclusive interviews.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eA MOOC on cardiac computed tomography (CT) is also available on this platform in order to introduce you to this complementary cardiovascular imaging technique.\u003c/p\u003e\n\u003cp\u003e本课程是与国际心血管磁共振学会（SCMR）合作开发的，适合想要深度了解心血管磁共振成像（CMR）的放射科医师，心内科及心外科医师，放射科技师/工程师和其他医疗健康专业人士。而无需具备CMR经验。\u003c/p\u003e\n\u003cp\u003e学习目标如下：\u003c/p\u003e\n\u003col\u003e\n\u003cli\u003e了解基本的CMR物理和序列知识，以便更好地了解如何获取心脏图像以及如何评估常用序列（例如，稳态自由进动序列，相位对比血流测量，T2 *和磁共振血管造影）。\u003c/li\u003e\n\u003cli\u003e了解CMR造影剂的安全性和风险。\u003c/li\u003e\n\u003cli\u003e具备SCMR 1级CMR图像分析能力，例如负荷灌注，延迟强化和心室功能后处理。\u003c/li\u003e\n\u003cli\u003e临床病例数据库中获取50个真实病例，利用专业后处理软件及学习平台提供的资料进行教学操作，获得实践经验。\u003c/li\u003e\n\u003cli\u003e对CMR领域未来发展的基本了解，如人工智能、特征追踪，以及T1和T2定量成像。\u003c/li\u003e\n\u003cli\u003e通过独家访谈获取知名CMR专家对学生的职业建议和想法。\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e此平台上还提供心脏计算机断层扫描（CT）的公开课，以全面介绍这两种优势互补的心血管成像技术。\u003c/p\u003e"])</script><script>self.__next_f.push([1,"3b4:T676,\u003cul\u003e\n\u003cli\u003eIntroduction of advanced techniques such as T1 and T2 mapping, feature tracking and exercise CMR.\u003c/li\u003e\n\u003cli\u003eThe different sequences used in cardiac MRI imaging and the physics behind these sequences.\u003c/li\u003e\n\u003cli\u003eHow to acquire the cardiac imaging planes.\u003c/li\u003e\n\u003cli\u003eHow to assess the ventricular function, late gadolinium enhancement and T2* for iron overload.\u003c/li\u003e\n\u003cli\u003eUnderstanding the normal appearances of the pericardium, heart muscle, valves and vasculature.\u003c/li\u003e\n\u003cli\u003eUnderstand how different cardiac pathologies result in different forms of cardiac remodelling.\u003c/li\u003e\n\u003cli\u003eAn overview of the main cardiac diseases, such as coronary artery disease, cardiomyopathies (eg. hypertrophic cardiomyopathy, dilated cardiomyopathy), valvular heart disease, cardiac tumours and congenital heart disease.\u003c/li\u003e\n\u003cli\u003e简介高级技术，例如T1和T2分布图，特征跟踪和运动负荷CMR。\u003c/li\u003e\n\u003cli\u003e心脏MRI成像中使用的不同序列及其物理背景知识。\u003c/li\u003e\n\u003cli\u003e心脏成像平面的获得方法。\u003c/li\u003e\n\u003cli\u003e如何分析心室功能、延迟强化以及利用 T2* 评价心肌铁负荷。\u003c/li\u003e\n\u003cli\u003e了解心包、心肌、瓣膜以及血管的正常表现。\u003c/li\u003e\n\u003cli\u003e明白不同的心肌疾病如何造成不同的心脏形态改变。\u003c/li\u003e\n\u003cli\u003e常见心脏疾病的概述，例如冠状动脉疾病，心肌病（例如肥厚性心肌病，扩张型心肌病），心脏瓣膜病，心脏肿瘤和先天性心脏病。\u003c/li\u003e\n\u003cli\u003e通过网络研讨会和论坛，了解并体验如何使用专用软件分析心脏图像。\u003c/li\u003e\n\u003cli\u003e利用正常志愿者和真实病例学习心室功能、血流和T1 /T2 mapping分析方法。\u003c/li\u003e\n\u003c/ul\u003e3b5:T644,\u003cp\u003ePreparing for the AP Biology exam requires a deep understanding of many different topics in biology as well as an understanding of the format of the AP exam and the types of questions it asks. This course is Part 4 of our AP Biology series designed to prepare you for the AP Biology exam. \u003c/p\u003e\n\u003cp\u003eIn Part 4, you will learn about ecology, the interactions between organisms,"])</script><script>self.__next_f.push([1," how they depend on each other, how they interact with their environment and how they compete with each other.\u003c/p\u003e\n\u003cp\u003eAs you work through this course, you will find lecture videos taught by expert AP Biology teachers, practice multiple choice questions and free response questions that are similar to what you will encounter on the AP exam and tutorial videos that show you step-by-step how to solve problems. By the end of the course, you will be prepared to take on the AP exam!\u003c/p\u003e\n\u003cp\u003eThis course is authorized as an Advanced Placement® (AP®) course by the AP Course Audit. The AP Course Audit was created by the College Board to give schools and students the confidence that all AP courses meet or exceed the same clearly articulated curricular expectations of colleges and universities.\u003c/p\u003e\n\u003cp\u003eBy taking an AP course and scoring successfully on the related AP Exam, students can:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eStand Out in College Admissions\u003c/li\u003e\n\u003cli\u003eEarn College Credits\u003c/li\u003e\n\u003cli\u003eSkip Introductory Classes\u003c/li\u003e\n\u003cli\u003eBuild College Skills\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cem\u003eAdvanced Placement® and AP® are trademarks registered and/or owned by the College Board, which was not involved in the production of, and does not endorse, these offerings.\u003c/em\u003e\u003c/p\u003e3b6:Tbfe,"])</script><script>self.__next_f.push([1,"\u003cp\u003e\u003cstrong\u003eDescription de ce cours : \u003c/strong\u003eChaque r\u0026eacute;gion du monde pr\u0026eacute;sente des facteurs de vuln\u0026eacute;rabilit\u0026eacute; au changement climatique mais est n\u0026eacute;anmoins en mesure d\u0026rsquo;att\u0026eacute;nuer les effets de ce ph\u0026eacute;nom\u0026egrave;ne et de renforcer sa r\u0026eacute;silience. En ratifiant l\u0026rsquo;Accord de Paris, la communaut\u0026eacute; internationale a manifest\u0026eacute; sa volont\u0026eacute; d\u0026rsquo;agir. En effet, sans action climatique concert\u0026eacute;e, les progr\u0026egrave;s accomplis pendant des d\u0026eacute;cennies en mati\u0026egrave;re de d\u0026eacute;veloppement seront menac\u0026eacute;s : nous nous trouvons donc \u0026agrave; un moment d\u0026eacute;cisif. Ce cours pr\u0026eacute;sente les donn\u0026eacute;es scientifiques les plus r\u0026eacute;centes sur la question, explique les diff\u0026eacute;rentes r\u0026eacute;percussions ressenties au plan r\u0026eacute;gional, d\u0026eacute;crit les strat\u0026eacute;gies d\u0026rsquo;action climatique et mentionne diff\u0026eacute;rents types d\u0026rsquo;action qui s\u0026rsquo;offrent \u0026agrave; vous.\u003c/p\u003e\r\n\u003cp\u003eLe cours \u0026laquo; Climat \u0026ndash; de la science \u0026agrave; l\u0026rsquo;action \u0026raquo; se d\u0026eacute;roule sur quatre semaines. Les deux premi\u0026egrave;res seront consacr\u0026eacute;es \u0026agrave; un tour d\u0026rsquo;horizon complet des donn\u0026eacute;es scientifiques disponibles sur le changement climatique, puis \u0026agrave; la description des effets du r\u0026eacute;chauffement propres \u0026agrave; certaines r\u0026eacute;gions au XXIe si\u0026egrave;cle. Les deux derni\u0026egrave;res semaines seront ax\u0026eacute;es sur les strat\u0026eacute;gies d\u0026rsquo;action que divers pays et r\u0026eacute;gions mettent en \u0026oelig;uvre pour relever le d\u0026eacute;fi climatique ainsi que sur la mani\u0026egrave;re dont chacun d\u0026rsquo;entre nous peut agir.\u003c/p\u003e\r\n\u003cp\u003e\u003cstrong\u003eFormat du cours\u003c/strong\u003e\u003c/p\u003e\r\n\u003cp\u003eCe MOOC est con\u0026ccedil;u selon un rythme hebdomadaire: cela inclut les ressources, les activit\u0026eacute;s et les exercices qui vous seront propos\u0026eacute;s. Chaque semaine, le mat\u0026eacute;riel p\u0026eacute;dagogique sera mis \u0026agrave; votre disposition :\u003c/p\u003e\r\n\u003cul\u003e\r\n\u003cli\u003eDes vid\u0026eacute;os interactives anim\u0026eacute;es par de grands sp\u0026eacute;cialistes et praticiens des questions climatiques;\u003c/li\u003e\r\n\u003cli\u003eDes ressources : activit\u0026eacute;s interactives fondamentales ou optionnelles (approfondies) sur le th\u0026egrave;me de la semaine;\u003c/li\u003e\r\n\u003cli\u003eDes questionnaires destin\u0026eacute;s \u0026agrave; \u0026eacute;valuer vos connaissances, compl\u0026eacute;ter vos nouvelles connaissances etvous permettre d\u0026rsquo;identifier les points \u0026agrave; revoir;\u003c/li\u003e\r\n\u003cli\u003eDes exercices qui affineront votre capacit\u0026eacute; d\u0026rsquo;analyse, de r\u0026eacute;flexion et de communication;\u003c/li\u003e\r\n\u003cli\u003eDes forums de discussion et des \u0026eacute;changes sur les m\u0026eacute;dias sociaux pour collaborer avec d\u0026rsquo;autres \u0026eacute;tudiants du monde entier, tout en enrichissant l\u0026rsquo;interaction entre les participants;\u003c/li\u003e\r\n\u003cli\u003eUne s\u0026eacute;ance de questions-r\u0026eacute;ponses interactive en direct avec des sp\u0026eacute;cialistes internationaux du changement climatique sur l\u0026rsquo;application Google Hangout;\u003c/li\u003e\r\n\u003cli\u003eEnfin, votre projet final consistera en un document num\u0026eacute;rique.\u003c/li\u003e\r\n\u003c/ul\u003e"])</script><script>self.__next_f.push([1,"3b7:T532,\u003cp\u003eCe MOOC, ax\u0026eacute; sur l\u0026rsquo;action, vous permettra d\u0026rsquo;am\u0026eacute;liorer votre connaissance des effets du changement climatique \u0026agrave; l\u0026rsquo;\u0026eacute;chelle r\u0026eacute;gionale et des strat\u0026eacute;gies sectorielles visant \u0026agrave; renforcer la r\u0026eacute;silience et \u0026agrave; promouvoir un avenir \u0026agrave; faible intensit\u0026eacute; de carbone. Vous aurez l\u0026rsquo;occasion d\u0026rsquo;approfondir ces questions et d\u0026rsquo;adapter votre apprentissage \u0026agrave; une ou plusieurs des r\u0026eacute;gions suivantes :\u003c/p\u003e\r\n\u003cul\u003e\r\n\u003cli\u003eAm\u0026eacute;rique latine et Cara\u0026iuml;bes\u003c/li\u003e\r\n\u003cli\u003eAfrique subsaharienne\u003c/li\u003e\r\n\u003cli\u003eMoyen-Orient et Afrique du Nord\u003c/li\u003e\r\n\u003cli\u003eEurope de l\u0026rsquo;Est et Asie centrale\u003c/li\u003e\r\n\u003cli\u003eAsie de l\u0026rsquo;Est et Pacifique\u003c/li\u003e\r\n\u003cli\u003eAsie du Sud\u003c/li\u003e\r\n\u003c/ul\u003e\r\n\u003cp\u003ePour ce faire, le MOOC r\u0026eacute;unit des scientifiques et des responsables de l\u0026rsquo;action publique renomm\u0026eacute;s et leur demande de pr\u0026eacute;senter une synth\u0026egrave;se des plus r\u0026eacute;centes donn\u0026eacute;es scientifiques sur le changement climatique, les strat\u0026eacute;gies r\u0026eacute;gionales de d\u0026eacute;veloppement \u0026agrave; faible intensit\u0026eacute; de carbone et \u0026agrave; l\u0026rsquo;\u0026eacute;preuve des al\u0026eacute;as climatiques dans tous les secteurs et une description g\u0026eacute;n\u0026eacute;rale de l\u0026rsquo;Accord de Paris et des r\u0026eacute;sultats de la COP 22.\u003c/p\u003e3b8:T5e3,\u003cp\u003eCuando se trata de herramientas para el análisis de datos, siempre tenemos las siguientes preguntas: ¿Cuál es la diferencia entre tantas herramientas que existen?¿Cuál es la mejor?¿Cuál deberia aprender?\u003c/p\u003e\n\u003cp\u003eLas funciones que realizan los científicos de datos incluyen la identificación de preguntas relevantes, la recopilación de datos de diferentes fuentes de datos, la organización de datos, la transformación de datos a la solución y la comunicación de estos hallazgos para tomar mejores decisiones comerciales.\u003c/p\u003e\n\u003cp\u003eLas herramientas de ciencia de datos o Data Science pueden ser de dos tipos:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eUno para aquellos que tienen conocimientos de programación.\u003c/li\u003e\n\u003c"])</script><script>self.__next_f.push([1,"li\u003eOtro para los usuarios comerciales.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eLas herramientas para el primer tipo, tienen que ver con el área de las tecnologías de información en donde se busca que la persona tenga conocimientos de algún lenguaje de programación como R o Python y comunmente a estas personas se les denomina científicos de datos.\u003c/p\u003e\n\u003cp\u003eLas herramientas que son para los usuarios comerciales se enfocan en automatizar el análisis de datos; en este tipo, los usuarios tienen conocimientos básicos de un lenguaje de programación, pero un fuerte conocimiento del área de dominio; por lo que se han empezado a llamar ciudadanos científicos de datos.\u003c/p\u003e\n\u003cp\u003eEstas herramientas te permitirán tomar las mejores decisiones basadas en el análisis de datos (también conocido como inteligencia de negocios).\u003c/p\u003e3b9:T6f9,\u003cp\u003eNominated for the 2020 edX Prize\u003c/p\u003e\r\n\r\n\u003cp\u003eIn this Professional Certificate program, you will learn the mechanics of how to design and facilitate projects using “pure” Agile Scrum and Lean Kanban techniques. You will also learn the trade-offs of using hybrid techniques such as Lean Startup, Scaled Agile For the Enterprise (SAFe), and Disciplined Agile Development. \u003c/p\u003e\r\n\r\n\u003cp\u003eWe will then go beyond these frameworks to the science and essential principles you’ll need to ensure you get the greatest benefits of Agile Project Management methods: Speed, Innovation, Leadership, and Kaizen (Change for the Better).\u003c/p\u003e\r\n\r\n\u003cp\u003eAfter completing this course series, you will be able to clearly explain how Agile techniques address faults in traditional project management techniques, the tradeoffs (benefits and risks) of these approaches, and when it’s best to apply them to maximize value to the organization.\u003c/p\u003e\r\n\r\n\u003cp\u003eEngineers, managers, designers, writers, creators, and executers of all types will benefit from learning these principles of Agile. Whether you’re delivering a small part of a project or portfolios of large multi-million-dollar government works; these principles scale and apply to all industries to ac"])</script><script>self.__next_f.push([1,"hieve delivery success. This is why companies that are embracing these principles continue to set record earnings and stock prices (e.g. AMZN, APPL, TSLA); and those that ignore them find themselves unable to compete.\u003c/p\u003e\r\n\r\n\u003cp\u003eUpon successful completion of this program, learners can earn up to 50 Professional Development Unit (PDU) credits, 10 PDU credits per course, which are recognized by the Project Management Institute (PMI). PDU credits are essential to those looking to maintain certification as a Project Management Professional (PMP). \u003c/p\u003e3ba:T56a,\u003cp\u003eLa ciencia de datos está transformando la manera en cómo las organizaciones trabajan con sus datos, ya que permite generar información más precisa, confiable, en tiempo real y que sustenta además de una toma de decisiones histórica, una estrategia proactiva. Con estas herramientas, las empresas modernas están automatizando procesos capaces de tomar decisiones autónomas lo que se convierte en una ventaja competitiva en el mercado actual.\u003c/p\u003e\r\n\r\n\u003cp\u003eEn este curso aprenderás no solo como funcionan las herramientas de la ciencia de datos (Data Science) sino aplicarlas de forma sencilla con uno de los ambientes de análisis mayormente aceptados como lo es “R”. El lenguaje R es un lenguaje de programación comunmente usado.\u003c/p\u003e\r\n\r\n\u003cp\u003eEn este programa de Certificación Profesional desarrollarás las actividades necesarias para aplicar la ciencia de datos y también aprenderás a través de casos prácticos cómo aprovechar mejor estas herramientas para el proceso de toma de decisiones.\u003c/p\u003e\r\n\r\n\u003cp\u003eLa metodología de este programa está pensanda para que sin importar tu nivel de conocimiento en el tema puedas alcanzar el nivel necesario para el análisis de datos en cada uno de los cursos en línea que lo componen.\u003c/p\u003e\r\n \r\n\u003cp\u003eTodas las herramientas del programa, compuesto por 3 cursos online, son de uso libre y corren en todas las plataformas de cómputo.\u003c/p\u003e3bb:T958,"])</script><script>self.__next_f.push([1,"\u003cp\u003e\u003cstrong\u003eMot de la conceptrice principale\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDurant les dernières années, de nombreux conflits armés et diverses crises humanitaires ont secoué notre planète et provoqué le déplacement forcé de nombreuses populations dans différentes régions du monde. Ces mouvements migratoires ont mis de nombreux pays face aux défis de l’accueil des réfugiés et des demandeurs d’asile. Les sociétés d’accueil se trouvent devant la nécessité de répondre aux divers besoins de ces populations afin de mieux les intégrer. Par conséquent, la connaissance et la prise en compte des réalités psychosociales et éducatives des jeunes réfugiés et demandeurs d’asile et de leur famille, ainsi que leur vécu pré, péri et post-migratoire constituent une assise pour toute action fructueuse auprès d’eux.\u003c/p\u003e\n\u003cp\u003eL’accueil et l’intégration des jeunes réfugiés et demandeurs d’asile dépendent du travail collaboratif de nombreux intervenants et professionnels qui doivent et veulent être formés et outillés à cet effet. Lors de l’arrivée des réfugiés syriens au Québec et au Canada (2015-2016), j’ai été très fréquemment sollicitée par les milieux éducatifs, les milieux de la santé et des services sociaux à proposer des formations ciblées à leurs intervenants. Après de multiples formations données au Québec ou ailleurs, j’ai voulu offrir et partager le fruit de nombreuses années de recherche et d’expérience clinique auprès de ces populations parfois endeuillées, traumatisées et vulnérabilisées par les expériences pré, péri et post-migratoires, mais aussi enrichies par des stratégies adaptatives. Ce CLOM (MOOC), ce cours en ligne organisé et massif, accessible, gratuit et adressé au monde francophone vient s’ajouter à toutes les initiatives visant un meilleur accueil et une meilleure intégration des jeunes réfugiés et demandeurs d’asile.\u003c/p\u003e\n\u003cp\u003eJ’espère que ce cours vous donnera les outils nécessaires pour intervenir de façon éclairée avec cette population particulière.\u003c/p\u003e\n\u003cp\u003eAu plaisir de partager ces contenus avec vous,\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGarine Papazian-Zohrabian | Professeure agrégée\u003cbr /\u003e\n\u003c/strong\u003e Département de psychopédagogie et d'andragogie\u003cbr /\u003e\nFaculté des sciences de l’éducation, Université de Montréal\u003cbr /\u003e\nMembre de l’Ordre des Psychologues du Québec\u003c/p\u003e"])</script><script>self.__next_f.push([1,"3bc:T8b3,"])</script><script>self.__next_f.push([1,"\u003cp\u003e\u003cstrong\u003eModule 1 : Les réfugiés et les demandeurs d’asile dans le monde : terminologie, contexte international, national et provincial\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eDéfinition des statuts\u003c/li\u003e\n\u003cli\u003eSituation des réfugiés dans le monde\u003c/li\u003e\n\u003cli\u003eLois et conventions internationales\u003c/li\u003e\n\u003cli\u003eL’éducation et la santé mentale des réfugiés dans le monde et au Canada\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eModule 2 : Les conflits armés, les guerres et les génocides et leurs conséquences sur la vie, l’éducation et la santé mentale des jeunes\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eConcepts et définitions\u003c/li\u003e\n\u003cli\u003eLes conflits armés et leurs conséquences\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eModule 3 : Les traumatismes pré, péri et post-migratoires : aspects cliniques, facteurs de risque et de protection\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eConcepts et définitions\u003c/li\u003e\n\u003cli\u003eSymptomatologie\u003c/li\u003e\n\u003cli\u003eApproches et pistes d’intervention\u003c/li\u003e\n\u003cli\u003ePrésentation de la grille d’analyse et analyse d’un cas d’un enfant traumatisé\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eModule 4 : Les deuils pré, péri et post-migratoires : aspects cliniques, facteurs de risque et de protection\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eDéfinitions et théories\u003c/li\u003e\n\u003cli\u003ePistes d’intervention\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eModule 5 : Les difficultés d’adaptation et d’apprentissage scolaire\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eDeuils, traumas et difficultés d’apprentissage et d’adaptation scolaire\u003c/li\u003e\n\u003cli\u003eMigration, santé mentale et expérience scolaire\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eModule 6 : Les défis et les enjeux de l’intégration des jeunes réfugiés\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eDéfis de l’accueil des réfugiés et des demandeurs d’asile\u003c/li\u003e\n\u003cli\u003eDéfis de la collaboration école-famille-communauté\u003c/li\u003e\n\u003cli\u003eRegards croisés sur les réalités et les défis vécus par les jeunes réfugiés et leurs familles\u003c/li\u003e\n\u003cli\u003eDéfis pour la formation et la gouvernance\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eModule 7 : Les pistes et les types d’accompagnement et d’intervention en milieu scolaire. Forces et limites de ces interventions\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003ePistes d’intervention en milieu scolaire\u003c/li\u003e\n\u003cli\u003eGroupes de parole en contexte scolaire\u003c/li\u003e\n\u003cli\u003eApproche transculturelle\u003c/li\u003e\n\u003cli\u003eLes programmes d’expression créatrice\u003c/li\u003e\n\u003c/ul\u003e"])</script><script>self.__next_f.push([1,"3bd:Td58,"])</script><script>self.__next_f.push([1,"\u003cp\u003eDans ce cours, vous explorerez et apprendrez les meilleures méthodes et pratiques des systèmes de recommandation, qui sont une composante essentielle de l’écosystème digital. Ce cours a été développé par IVADO et HEC Montréal dans le cadre d’un atelier qui a eu lieu à Montréal. Vous serez accompagné.e tout au long du processus par sept experts internationaux du milieu universitaire et de l’industrie qui vous fourniront des exemples concrets. \u003c/p\u003e\n\u003cp\u003eLes systèmes de recommandation sont des algorithmes qui trouvent des tendances dans le comportement des utilisateurs pour améliorer les expériences personnalisées et comprendre leur environnement. Ils sont omniprésents et sont le plus souvent utilisés pour recommander des items aux utilisateurs, notamment des livres et des films, mais aussi des amis potentiels, des recettes de cuisine ou même de la documentation pertinente pour de grands projets de logiciels, ou des articles intéressant les scientifiques.\u003c/p\u003e\n\u003cp\u003eLe contenu de ce MOOC est une introduction au domaine des systèmes de recommandation. Le programme comprend : l’apprentissage automatique pour les systèmes de recommandation, suivi d’une introduction aux méthodes d’évaluation; la modélisation avancée; les bandits contextuels; les méthodes de classement; l’équité et la discrimination dans les systèmes de recommandation. \u003c/p\u003e\n\u003cp\u003eLe cours s’adresse principalement aux professionnel.le.s du secteur et aux étudiant.e.s universitaires ayant des connaissances de base (première année de baccalauréat) en mathématiques et en programmation (idéalement Python). Les diplômé.e.s en sciences et en ingénierie (principalement celles et ceux qui ne sont pas encore familiers avec l’apprentissage automatique et les systèmes de recommandation) trouveront ce contenu instructif et intéressant. Le contenu de ce cours sera également d’une grande utilité pour toute personne qui s’intéresse à l’IA ou qui l’utilise, de quelque manière que ce soit.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNous estimons qu’il faut 6 semaines pour compléter ce cours.\u003c/strong\u003e Le cours est divisé en segments que vous pourrez visionner à votre propre rythme. Afin d’évaluer votre compréhension du contenu, des questionnaires complets seront proposés à la fin de chaque segment. Vous pourrez également pratiquer les algorithmes des systèmes de recommandation grâce à un tutoriel guidé par un expert. De plus, un deuxième module de pratique individuelle sera offert aux participant.e.s qui s’inscrivent au cours avec le certificat vérifié. \u003c/p\u003e\n\u003cp\u003eNous vous souhaitons la bienvenue dans ce parcours d’apprentissage de Systèmes de recommandation : Derrière l’écran!\u003c/p\u003e\n\u003cp\u003eCe cours vous est présenté par IVADO, HEC Montréal et l’Université de Montréal.\u003ca href=\"https://ivado.ca/en/\" rel=\"noopener\" target=\"_blank\"\u003e\u003c/a\u003e\u003c/p\u003e\n\u003cp\u003eIVADO est un institut collaboratif québécois dans le domaine de l’intelligence numérique.\u003ca href=\"https://www.hec.ca/en/index.html\" rel=\"noopener\" target=\"_blank\"\u003e\u003c/a\u003e\u003c/p\u003e\n\u003cp\u003eHEC Montréal est une université francophone de renommée internationale qui offre des formations et des programmes de recherche dans le domaine de la gestion. \u003ca href=\"https://www.umontreal.ca/en/\" rel=\"noopener\" target=\"_blank\"\u003e\u003c/a\u003e\u003c/p\u003e\n\u003cp\u003eL’Université de Montréal est l’une des principales universités de recherche au monde.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"3be:T9f5,"])</script><script>self.__next_f.push([1,"\u003cp\u003ePartout autour de nous se forment des collectifs d’habitants, d’usagers, de citoyens. Certains inventent des réponses aux besoins fondamentaux: se nourrir, se loger, se mouvoir, générer des revenus, accéder aux services d’éducation, préserver la santé. D’autres se demandent comment renouveler les façons de consommer, de produire, de travailler, de vivre ensemble... pour répondre aux enjeux du changement climatique et de la raréfaction des ressources. \u003c/p\u003e\n\u003cp\u003eLes communs sont des sujets collectifs, des systèmes d’action, mais aussi des lieux et des formes spatiales et paysagères. De la cour africaine à la cage d’escalier de la tour HLM, des friches industrielles aux intérieurs d’îlots d’habitat, des délaissés urbains aux patrimoines paysagers et aux multiples espaces de production de la ville nourricière, nous apprendrons à identifier, à nommer et à décrire ces lieux, à discerner dans quelle mesure ils sont (ou pas) moteurs de changement et contribuent (ou pas) à la recomposition des structures territoriales. \u003c/p\u003e\n\u003cp\u003eNous allons explorer ensemble cet univers de pratiques en mettant en résonance l’approche des sciences sociales et celle de l’urbanisme. Nous poserons ensemble des balises méthodologiques vous permettant de repérer les communs actifs dans votre environnement, d’en décrire les différentes dimensionsavec un regard critique, et d’en évaluer les potentiels de transformation territoriale. Le cours présentera de nombreux exemples. \u003c/p\u003e\n\u003cp\u003ePour les apprenant.esqui poursuivent le certificat, nous vous inviterons, à travers un exercice évolutif en rapport avec votre expérience individuelle, à réaliser un récit audiovisuel sur la question des communs. \u003c/p\u003e\n\u003cp\u003eCe cours s’adresse : \u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eaux titulaires d’un diplôme de 2ème cycle universitaire (toutes disciplinaires confondues) qui cherchent un complément de formation ouvrant sur l’organisation de l’espace comme support de processus de développement social, économique et culturel,\u003c/li\u003e\n\u003cli\u003eaux urbanistes et/ou aménageurs désireux d’améliorer l’intégration des dimensions sociale et environnementale de l’aménagement de l’espace,\u003c/li\u003e\n\u003cli\u003eaux professionnels du secteur du développement qui souhaitent prendre en compte la diversité des pratiques et des conceptions du développement et apprendre à en intégrer davantage la dimension spatiale.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eIntéressé*e ? Alors bienvenue et au plaisir de vous rencontrer prochainement dans le cadre du cours !\u003c/p\u003e"])</script><script>self.__next_f.push([1,"3bf:T693,\u003cp\u003eDo you know what artificial intelligence (AI) means for your organization? It isn’t about robots taking jobs or replacing your workforce. AI is simply the process of programming a computer to make decisions for itself, which can make your business operations more efficient. Need a strategy to effectively implement AI technologies into your company? Then this artificial intelligence program is the one for you. The Artificial Intelligence: Implications for Business Strategy online short course from the MIT Sloan School of Management and the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) will show you how to capitalize on the value automation offers. It explores the potential of robotics, natural language processing, and machine learning (ML), and equips you with the knowledge and confidence to include them in your business strategy. Most importantly, this course will guide the creation of a road map for the implementation of AI and ML in your organization and provide you with the skills to drive innovation forward.This AI course looks at the organizational and managerial implications of the technologies. It’s aimed at managers, executives, and business leaders rather than those in tech or IT roles. So, you don’t need to be a software engineer or data scientist to keep up with the content. On this program, you’ll learn how AI and ML can be applied in the workplace to augment current operations. It’s about developing strategic decision-making skills about the use of these technologies in your business, analyzing their potential impact, and building the language to articulate your insights with your teams and organization.\u003c/p\u003e3c0:Tcef,"])</script><script>self.__next_f.push([1,"\u003cp\u003eImproving prediction is one of the key challenges the medical industry faces in advancing patient care. Enhancing diagnosis, individualizing treatments, and understanding disease progression are all matters of prediction, an area where machine learning (ML) and artificial intelligence (AI) excel.1\u003c/p\u003e\n\u003cp\u003eDiscover the impact AI innovations can have in medicine — on both traditional health care systems and decision-making approaches — with the Artificial Intelligence in Health Care online short course from the MIT Sloan School of Management and the MIT J-Clinic. \u003c/p\u003e\n\u003cp\u003eThrough industry case studies, you’ll better understand AI’s applications and limitations, examine the challenges AI can help overcome, and explore how it’s already been successfully deployed in the sector. \u003c/p\u003e\n\u003cp\u003eYou’ll gain insight and knowledge from MIT, an institution renowned for developing ML methods with applications in health care. Regina Barzilay, your Faculty Director, is also globally recognized for her work in AI and breast cancer detection. \u003c/p\u003e\n\u003cp\u003e\u003cem\u003e1\u003ca href=\"https://www.technologyreview.com/s/613361/giving-medicine-a-dose-of-ai/\" target=\"_blank\"\u003eMIT Technology Review\u003c/a\u003e (Apr, 2019).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWhether you work in business or medicine, this course will give you an understanding of the transformative role that AI and ML can play in the health care industry. Professionals working in the health sector will benefit from an understanding of the types of problems that AI techniques can help solve. This program covers key topics such as the basics of ML, neural networks, and deep learning. The knowledge gained throughout this course can be immediately and directly applied to roles within the health care sector. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMachine learning:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eML is a field of artificial intelligence that uses algorithms to learn from and make predictions on data. This course will introduce you to machine learning algorithms and how they are used in the health care industry. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNeural networks:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe MIT Sloan Artificial Intelligence in Health Care online course provides insights into the different types of neural networks and how they can be applied to health care data. Neural networks are a type of machine learning algorithm that are particularly well suited for tasks such as image recognition and classification. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeep learning:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAdditionally, the AI in health care course will cover the basics of deep learning. Deep learning is the process of using artificial neural networks with many layers to learn complex patterns in data. It is a subfield of machine learning that is concerned with algorithms that learn from data that is unstructured or unlabelled. This course will introduce you to deep learning methods and how they are used in the health care industry. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComputer science professionals:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe course is taught by computer science experts from MIT and the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). CSAIL is one of the world’s leading centers for artificial intelligence research. The faculty members teaching this course are at the forefront of their field and are developing cutting-edge technology that is being used in multiple industries today.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"3c1:T591,\u003cp\u003eMachine learning offers an opportunity to gain a powerful competitive edge in business and is increasingly becoming a priority for managers and executives. In the Machine Learning in Business online short course from the MIT Sloan School of Management and the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), you’ll be guided to discover the business potential of machine learning while developing strategies for effective implementation.\u003c/p\u003e\n\u003cp\u003eThe program focuses on the managerial implications of machine learning and touches on certain technical aspects to provide you with the deeper knowledge needed to craft an effective machine learning integration strategy. Explore the value and impact of this technology, with insights from esteemed MIT faculty and machine learning experts. \u003c/p\u003e\n\u003cp\u003eAlthough not technical in focus, this online short course will be useful for leaders and decision makers who want to gain a grounding in machine learning to successfully integrate it into their organization. It’s also relevant for managers, data specialists, consultants, and business professionals interested in exploring the technology’s strategic implications. You’ll walk away with a sound understanding of the applications of machine learning in business, without needing to code or program. You’ll also explore the opportunities, capabilities, and scope of this transformative technology.\u003c/p\u003e3c2:T630,\u003cp\u003eHuman-Computer Interaction (HCI) has evolved extensively over time. Along with advancements in technology, HCI has the potential to transform our experience with machines by creating simpler, more powerful, and intuitive digital experiences.\u003c/p\u003e\n\u003cp\u003eThe \u003cstrong\u003eHuman-Computer Interaction for User Experience Design\u003c/strong\u003e online short course from the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) helps you reflect on the current state of user and computer interaction. Eight experts from MIT CSAIL have dedicated their research efforts to exploring the ways in which HCI can be"])</script><script>self.__next_f.push([1," enhanced, and they’re opening that research up to you through this online course so you can apply it for improved user experience (UX) and user interface (UI) design.\u003c/p\u003e\n\u003cp\u003eGuided by their industry insight, you’ll have the opportunity to imagine the future of HCI by reflecting on non-traditional interaction, speech recognition, and rapid prototyping, among others. Over the course of six weeks online, you’ll examine real-world applications of technology aimed at bettering UX and UI design, as you take your understanding beyond interface by integrating future-focused HCI into your work.\u003c/p\u003e\n\u003cp\u003eThis program is designed to equip those who are interested in understanding the latest HCI research as part of their professional education, or are looking to explore a new career in human-computer interaction. Industry UX designers also stand to benefit by exploring HCI thinking and real-world applications, empowering them to conceptualize better interface designs.\u003c/p\u003e3c3:T686,\u003cp\u003eTraining artificial intelligence (AI) models has traditionally required large sets of annotated data. As a result, small, uncurated data — which carries untapped value — is often left untouched. By leveraging cutting-edge developments in machine learning (ML), you can unlock the latent potential of data from unused sources to create competitive opportunities for your business. \u003c/p\u003e\n\u003cp\u003eThe \u003cstrong\u003eUnsupervised Machine Learning: Unlocking the Potential of Data\u003c/strong\u003e online short course from the MIT Sloan School of Management and the MIT Schwarzman College of Computing explores the technical and strategic considerations of unsupervised learning approaches. In just six weeks, you’ll study these approaches, their capabilities, use cases, limitations, and applications. You’ll learn to see the potential of your data — no matter its quantity or quality — and deploy AI solutions tailored to your unique data, problem, and business. \u003c/p\u003e\n\u003cp\u003eThis program is designed to help business decision makers leverage opportunities created by unsupe"])</script><script>self.__next_f.push([1,"rvised ML. Understanding how to leverage uncurated data, managers and technology leads will be able to plan new data acquisition protocols. IT and tech professionals looking for up-to-date developments in unsupervised learning will benefit from this program material, as will data scientists and analysts looking to strengthen their knowledge of the application of computer vision technologies.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe ability to code is not a prerequisite for this program. However, this program contains complex concepts that require an existing understanding and above-average knowledge of machine learning.\u003c/em\u003e\u003c/p\u003e3c4:T43a,\u003cp\u003eAre you interested in learning to code? Our coding bootcamp is rigorous and fast-paced, exploring both the theory and application of web development. As you gain proficiency, you’ll use what you learn to build complex projects under the guidance of instructors who are professional web developers. You will complete the program with an impressive professional portfolio, and you will have access to career guidance as you begin your journey to becoming a web development professional.\u003c/p\u003e\r\n\u003cul\u003e\r\n\u003cli\u003eLearn in-demand skills through a competitive curriculum: HTML5, CSS3, JavaScript, jQuery, Express.js, React.js, Node.js, Progressive Web Applications, Agile Development, Computer Science applied to JavaScript, database management, MongoDB, MySQL, Git, and more.*\u003c/li\u003e\r\n\u003cli\u003eBuild a portfolio of web applications to showcase your knowledge, and benefit from a wide range of career services to position you for success.\u003c/li\u003e\r\n\u003cli\u003eGain access to continuation courses that cover additional market-driven technologies, including Python, Java, C#, and Amazon Web Services.\u003c/li\u003e\r\n\u003c/ul\u003e3c5:T435,\u003cp\u003eAre you interested in learning to code? Our coding bootcamp is rigorous and fast-paced, exploring both the theory and application of web development. As you gain proficiency, you’ll use what you learn to build complex projects under the guidance of instructors who are professional web developers. You will complete the program with "])</script><script>self.__next_f.push([1,"an impressive professional portfolio, and you will have access to career guidance as you begin your journey to becoming a web development professional.\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eLearn in-demand skills through a competitive curriculum: HTML5, CSS3, JavaScript, jQuery, Express.js, React.js, Node.js, Progressive Web Applications, Agile Development, Computer Science applied to JavaScript, database management, MongoDB, MySQL, Git, and more.*\u003c/li\u003e\n\u003cli\u003eBuild a portfolio of web applications to showcase your knowledge, and benefit from a wide range of career services to position you for success.\u003c/li\u003e\n\u003cli\u003eGain access to continuation courses that cover additional market-driven technologies, including Python, Java, C#, and Amazon Web Services.\u003c/li\u003e\n\u003c/ul\u003e3c6:T435,\u003cp\u003eAre you interested in learning to code? Our coding bootcamp is rigorous and fast-paced, exploring both the theory and application of web development. As you gain proficiency, you’ll use what you learn to build complex projects under the guidance of instructors who are professional web developers. You will complete the program with an impressive professional portfolio, and you will have access to career guidance as you begin your journey to becoming a web development professional.\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eLearn in-demand skills through a competitive curriculum: HTML5, CSS3, JavaScript, jQuery, Express.js, React.js, Node.js, Progressive Web Applications, Agile Development, Computer Science applied to JavaScript, database management, MongoDB, MySQL, Git, and more.*\u003c/li\u003e\n\u003cli\u003eBuild a portfolio of web applications to showcase your knowledge, and benefit from a wide range of career services to position you for success.\u003c/li\u003e\n\u003cli\u003eGain access to continuation courses that cover additional market-driven technologies, including Python, Java, C#, and Amazon Web Services.\u003c/li\u003e\n\u003c/ul\u003e3c7:T435,\u003cp\u003eAre you interested in learning to code? Our coding bootcamp is rigorous and fast-paced, exploring both the theory and application of web development. As you gain proficiency, you’ll use what you learn to build"])</script><script>self.__next_f.push([1," complex projects under the guidance of instructors who are professional web developers. You will complete the program with an impressive professional portfolio, and you will have access to career guidance as you begin your journey to becoming a web development professional.\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eLearn in-demand skills through a competitive curriculum: HTML5, CSS3, JavaScript, jQuery, Express.js, React.js, Node.js, Progressive Web Applications, Agile Development, Computer Science applied to JavaScript, database management, MongoDB, MySQL, Git, and more.*\u003c/li\u003e\n\u003cli\u003eBuild a portfolio of web applications to showcase your knowledge, and benefit from a wide range of career services to position you for success.\u003c/li\u003e\n\u003cli\u003eGain access to continuation courses that cover additional market-driven technologies, including Python, Java, C#, and Amazon Web Services.\u003c/li\u003e\n\u003c/ul\u003e3c8:T435,\u003cp\u003eAre you interested in learning to code? 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Our coding b"])</script><script>self.__next_f.push([1,"ootcamp is rigorous and fast-paced, exploring both the theory and application of web development. As you gain proficiency, you’ll use what you learn to build complex projects under the guidance of instructors who are professional web developers. 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That's why we've designed a skills-based learning program that not only equips you with the latest analytics tools and technique"])</script><script>self.__next_f.push([1,"s but also connects you with industry micro-credentials that are in high demand.\r\nBecome a data analyst ready to analyze and to visualize data for strategic decision making \r\nStudy contemporary data analyst skills from content derived from leading, global organizations\r\nStudy consumers’ buying habits to help businesses make more strategic decisions about how they market their products and services. \r\nMaster the process of gleaning insights from data to inform better business decisions\r\nLearn in-demand job skills from first day of instruction and bring them into the workplace\r\nThe Masters of Science in Business Analytics is designed to prepare learners for data analyst careers. A data analyst finds a solution to a problem or provides an answer to a question. This career tasks a data analyst to gather, purify, and analyze data sets. Contemporary data analysts work in a variety of fields, including government, business, finance, law enforcement, and science.3df:Ta08,"])</script><script>self.__next_f.push([1,"Louisiana State University is a Top 100 Public University with a dedicated focus on student involvement, research opportunities, and experiential learning. With more than 330 fields of study and 70 majors, LSU offers students opportunities for hands-on experience working alongside world-class faculty. Top-ranked and popular programs include business, engineering, petroleum engineering, and STEM.\n-In an undergraduate computer science degree, students learn programming, software engineering, computer organization, databases, computer networks, artificial intelligence, and mathematics. The program includes lectures, lab work, and projects.\n-Programming languages: Students learn to write code in various programming languages, such as Java, Python, and C++, and to apply programming constructs such as loops, functions, and conditionals to solve problems.\n-Data structures and algorithms: Students learn how to represent and manipulate data efficiently using structures such as arrays, lists, stacks, queues, and trees, and how to design and analyze algorithms for searching, sorting, and graph traversal.\n-Software engineering principles: Students learn how to apply principles of software engineering, such as design patterns, testing, and version control, to build maintainable and scalable software systems.\n-Computer organization and architecture: Students learn how computers work at a low level, including topics such as digital logic, instruction set architecture, and memory hierarchy.\n-Operating systems: Students learn about the design and implementation of operating systems, including topics such as process management, memory management, and file systems.\n-Databases: Students learn how to design and use databases to store, manipulate, and retrieve data using query languages such as SQL and to work with different database management systems such as MySQL and Oracle.\n-Computer networks: Students learn how to design and manage computer networks, including topics such as TCP/IP, routing, and network security.\n-Artificial intelligence: Students learn about the principles and applications of artificial intelligence, including machine learning, natural language processing, and computer vision.\n-Mathematics: Students learn mathematical concepts and methods that are foundational to computer science, such as discrete mathematics, calculus, and linear algebra.\n-Web development: Students learn how to design and develop web applications using languages and tools such as HTML, CSS, JavaScript, and web frameworks such as Django and Ruby on Rails."])</script><script>self.__next_f.push([1,"3e0:T966,"])</script><script>self.__next_f.push([1,"- #147 National Universities - U.S. News \u0026 World Report, 2019\n- A true campus experience just minutes from the cultural and financial capital of the world\n- 240+ major companies recruit on campus Apple, IBM, AIG, Pepsi and Merrill Lynch\n-In an undergraduate computer science degree, students learn programming, software engineering, computer organization, databases, computer networks, artificial intelligence, and mathematics. The program includes lectures, lab work, and projects.\n-Programming languages: Students learn to write code in various programming languages, such as Java, Python, and C++, and to apply programming constructs such as loops, functions, and conditionals to solve problems.\n-Data structures and algorithms: Students learn how to represent and manipulate data efficiently using structures such as arrays, lists, stacks, queues, and trees, and how to design and analyze algorithms for searching, sorting, and graph traversal.\n-Software engineering principles: Students learn how to apply principles of software engineering, such as design patterns, testing, and version control, to build maintainable and scalable software systems.\n-Computer organization and architecture: Students learn how computers work at a low level, including topics such as digital logic, instruction set architecture, and memory hierarchy.\n-Operating systems: Students learn about the design and implementation of operating systems, including topics such as process management, memory management, and file systems.\n-Databases: Students learn how to design and use databases to store, manipulate, and retrieve data using query languages such as SQL and to work with different database management systems such as MySQL and Oracle.\n-Computer networks: Students learn how to design and manage computer networks, including topics such as TCP/IP, routing, and network security.\n-Artificial intelligence: Students learn about the principles and applications of artificial intelligence, including machine learning, natural language processing, and computer vision.\n-Mathematics: Students learn mathematical concepts and methods that are foundational to computer science, such as discrete mathematics, calculus, and linear algebra.\n-Web development: Students learn how to design and develop web applications using languages and tools such as HTML, CSS, JavaScript, and web frameworks such as Django and Ruby on Rails."])</script><script>self.__next_f.push([1,"3e1:T9f5,"])</script><script>self.__next_f.push([1,"The University of Illinois Chicago provides a hands-on learning experience in a supportive, diverse environment. Located in downtown Chicago, UIC offers you the opportunity to live, learn, and excel in the third-largest city in the US. UIC’s top-ranked programs include engineering, business, architecture, design, education, health sciences, public health, and public affairs.\n-In an undergraduate computer science degree, students learn programming, software engineering, computer organization, databases, computer networks, artificial intelligence, and mathematics. The program includes lectures, lab work, and projects.\n-Programming languages: Students learn to write code in various programming languages, such as Java, Python, and C++, and to apply programming constructs such as loops, functions, and conditionals to solve problems.\n-Data structures and algorithms: Students learn how to represent and manipulate data efficiently using structures such as arrays, lists, stacks, queues, and trees, and how to design and analyze algorithms for searching, sorting, and graph traversal.\n-Software engineering principles: Students learn how to apply principles of software engineering, such as design patterns, testing, and version control, to build maintainable and scalable software systems.\n-Computer organization and architecture: Students learn how computers work at a low level, including topics such as digital logic, instruction set architecture, and memory hierarchy.\n-Operating systems: Students learn about the design and implementation of operating systems, including topics such as process management, memory management, and file systems.\n-Databases: Students learn how to design and use databases to store, manipulate, and retrieve data using query languages such as SQL and to work with different database management systems such as MySQL and Oracle.\n-Computer networks: Students learn how to design and manage computer networks, including topics such as TCP/IP, routing, and network security.\n-Artificial intelligence: Students learn about the principles and applications of artificial intelligence, including machine learning, natural language processing, and computer vision.\n-Mathematics: Students learn mathematical concepts and methods that are foundational to computer science, such as discrete mathematics, calculus, and linear algebra.\n-Web development: Students learn how to design and develop web applications using languages and tools such as HTML, CSS, JavaScript, and web frameworks such as Django and Ruby on Rails."])</script><script>self.__next_f.push([1,"3e2:Ta0b,"])</script><script>self.__next_f.push([1,"Gonzaga University’s humanistic heritage focuses on educating the mind, body, and spirit, and developing personal, academic, and professional growth through critical thought and creative innovation. Gonzaga University’s humanistic heritage focuses on educating the mind, body, and spirit, and developing personal, academic, and professional growth through critical thought and creative innovation.\n-In an undergraduate computer science degree, students learn programming, software engineering, computer organization, databases, computer networks, artificial intelligence, and mathematics. The program includes lectures, lab work, and projects.\n-Programming languages: Students learn to write code in various programming languages, such as Java, Python, and C++, and to apply programming constructs such as loops, functions, and conditionals to solve problems.\n-Data structures and algorithms: Students learn how to represent and manipulate data efficiently using structures such as arrays, lists, stacks, queues, and trees, and how to design and analyze algorithms for searching, sorting, and graph traversal.\n-Software engineering principles: Students learn how to apply principles of software engineering, such as design patterns, testing, and version control, to build maintainable and scalable software systems.\n-Computer organization and architecture: Students learn how computers work at a low level, including topics such as digital logic, instruction set architecture, and memory hierarchy.\n-Operating systems: Students learn about the design and implementation of operating systems, including topics such as process management, memory management, and file systems.\n-Databases: Students learn how to design and use databases to store, manipulate, and retrieve data using query languages such as SQL and to work with different database management systems such as MySQL and Oracle.\n-Computer networks: Students learn how to design and manage computer networks, including topics such as TCP/IP, routing, and network security.\n-Artificial intelligence: Students learn about the principles and applications of artificial intelligence, including machine learning, natural language processing, and computer vision.\n-Mathematics: Students learn mathematical concepts and methods that are foundational to computer science, such as discrete mathematics, calculus, and linear algebra.\n-Web development: Students learn how to design and develop web applications using languages and tools such as HTML, CSS, JavaScript, and web frameworks such as Django and Ruby on Rails."])</script><script>self.__next_f.push([1,"3e3:T9fa,"])</script><script>self.__next_f.push([1,"The University of South Carolina is a globally recognized, high-impact research university committed to a superior student experience and dedicated to innovation in learning, research, and community engagement. UofSC offers 350+ degree programs and is one of only 40 public universities to receive Carnegie Classifications for both top-tier research activity and community engagement.\n-In an undergraduate computer science degree, students learn programming, software engineering, computer organization, databases, computer networks, artificial intelligence, and mathematics. The program includes lectures, lab work, and projects.\n-Programming languages: Students learn to write code in various programming languages, such as Java, Python, and C++, and to apply programming constructs such as loops, functions, and conditionals to solve problems.\n-Data structures and algorithms: Students learn how to represent and manipulate data efficiently using structures such as arrays, lists, stacks, queues, and trees, and how to design and analyze algorithms for searching, sorting, and graph traversal.\n-Software engineering principles: Students learn how to apply principles of software engineering, such as design patterns, testing, and version control, to build maintainable and scalable software systems.\n-Computer organization and architecture: Students learn how computers work at a low level, including topics such as digital logic, instruction set architecture, and memory hierarchy.\n-Operating systems: Students learn about the design and implementation of operating systems, including topics such as process management, memory management, and file systems.\n-Databases: Students learn how to design and use databases to store, manipulate, and retrieve data using query languages such as SQL and to work with different database management systems such as MySQL and Oracle.\n-Computer networks: Students learn how to design and manage computer networks, including topics such as TCP/IP, routing, and network security.\n-Artificial intelligence: Students learn about the principles and applications of artificial intelligence, including machine learning, natural language processing, and computer vision.\n-Mathematics: Students learn mathematical concepts and methods that are foundational to computer science, such as discrete mathematics, calculus, and linear algebra.\n-Web development: Students learn how to design and develop web applications using languages and tools such as HTML, CSS, JavaScript, and web frameworks such as Django and Ruby on Rails."])</script><script>self.__next_f.push([1,"3e4:Tb2b,"])</script><script>self.__next_f.push([1,"Western New England University offers a hands-on and personalized educational experience, with small class sizes and nurturing faculty. The 215-acre campus offers a vibrant community where students can explore cutting-edge research, entrepreneurial prospects, and creative pursuits, all while building a wide professional network. With degree programs in high-demand fields such as engineering, health, pharmaceuticals, and business, Western New England University prepares students to get started on their career journey. Learn from industry professionals as you develop key skills and gain in-depth knowledge that will help you stand out to employers in the US, or anywhere in the world.\n-In an undergraduate computer science degree, students learn programming, software engineering, computer organization, databases, computer networks, artificial intelligence, and mathematics. The program includes lectures, lab work, and projects.\n-Programming languages: Students learn to write code in various programming languages, such as Java, Python, and C++, and to apply programming constructs such as loops, functions, and conditionals to solve problems.\n-Data structures and algorithms: Students learn how to represent and manipulate data efficiently using structures such as arrays, lists, stacks, queues, and trees, and how to design and analyze algorithms for searching, sorting, and graph traversal.\n-Software engineering principles: Students learn how to apply principles of software engineering, such as design patterns, testing, and version control, to build maintainable and scalable software systems.\n-Computer organization and architecture: Students learn how computers work at a low level, including topics such as digital logic, instruction set architecture, and memory hierarchy.\n-Operating systems: Students learn about the design and implementation of operating systems, including topics such as process management, memory management, and file systems.\n-Databases: Students learn how to design and use databases to store, manipulate, and retrieve data using query languages such as SQL and to work with different database management systems such as MySQL and Oracle.\n-Computer networks: Students learn how to design and manage computer networks, including topics such as TCP/IP, routing, and network security.\n-Artificial intelligence: Students learn about the principles and applications of artificial intelligence, including machine learning, natural language processing, and computer vision.\n-Mathematics: Students learn mathematical concepts and methods that are foundational to computer science, such as discrete mathematics, calculus, and linear algebra.\n-Web development: Students learn how to design and develop web applications using languages and tools such as HTML, CSS, JavaScript, and web frameworks such as Django and Ruby on Rails."])</script><script>self.__next_f.push([1,"3e5:T4c2,Technology powers our world, touching every aspect of our lives. So it’s no \r\nwonder that qualified computer science professionals are in such high \r\ndemand.\r\n\r\nNow you can start your technology career strong with an online Bachelor of \r\nScience in Computer Science from Maryville University. Designed with input \r\nfrom top employers, along with experienced instructors from our John E. \r\nSimon School of Business and College of Arts and Sciences, our flexible, \r\nstate-of-the-art program can help you gain the technical, problem-solving, \r\nand critical thinking skills you need to pursue top jobs in tech.\r\n\r\nBuild your foundation in key competencies such as computer architecture, \r\nsecurity, programming, and web design. Benefit from experiential learning \r\nopportunities so you can apply what you’ve learned in real-world \r\nprofessional settings. And tailor your education to your interests and \r\ngoals with a choice of six computer science certificates built right into \r\nthe curriculum.\r\n\r\nWhen you earn your B.S. in computer science degree from Maryville, you put \r\nyourself in a position to build the world of tomorrow and embark on an \r\nexciting and financially rewarding career.\r\n\r\nGet Curriculum Details3e6:T99c,"])</script><script>self.__next_f.push([1,"The University of Kansas is a top-tier public research university with a commitment to a research-focused academic curriculum and career support. At KU, you can choose from over 190 fields of study, including top-ranked business, engineering, pharmacy, education, and architecture programs.\n-In an undergraduate computer science degree, students learn programming, software engineering, computer organization, databases, computer networks, artificial intelligence, and mathematics. The program includes lectures, lab work, and projects.\n-Programming languages: Students learn to write code in various programming languages, such as Java, Python, and C++, and to apply programming constructs such as loops, functions, and conditionals to solve problems.\n-Data structures and algorithms: Students learn how to represent and manipulate data efficiently using structures such as arrays, lists, stacks, queues, and trees, and how to design and analyze algorithms for searching, sorting, and graph traversal.\n-Software engineering principles: Students learn how to apply principles of software engineering, such as design patterns, testing, and version control, to build maintainable and scalable software systems.\n-Computer organization and architecture: Students learn how computers work at a low level, including topics such as digital logic, instruction set architecture, and memory hierarchy.\n-Operating systems: Students learn about the design and implementation of operating systems, including topics such as process management, memory management, and file systems.\n-Databases: Students learn how to design and use databases to store, manipulate, and retrieve data using query languages such as SQL and to work with different database management systems such as MySQL and Oracle.\n-Computer networks: Students learn how to design and manage computer networks, including topics such as TCP/IP, routing, and network security.\n-Artificial intelligence: Students learn about the principles and applications of artificial intelligence, including machine learning, natural language processing, and computer vision.\n-Mathematics: Students learn mathematical concepts and methods that are foundational to computer science, such as discrete mathematics, calculus, and linear algebra.\n-Web development: Students learn how to design and develop web applications using languages and tools such as HTML, CSS, JavaScript, and web frameworks such as Django and Ruby on Rails."])</script><script>self.__next_f.push([1,"3e7:T9d9,"])</script><script>self.__next_f.push([1,"Auburn University prepares you for success with its prestigious academic programs, emphasis on hands-on learning experiences, and family spirit. Auburn University offers more than 150 undergraduate degrees, including top-ranked programs in engineering, business, supply chain management, journalism, architecture and design, and fisheries/aquaculture.\n-In an undergraduate computer science degree, students learn programming, software engineering, computer organization, databases, computer networks, artificial intelligence, and mathematics. The program includes lectures, lab work, and projects.\n-Programming languages: Students learn to write code in various programming languages, such as Java, Python, and C++, and to apply programming constructs such as loops, functions, and conditionals to solve problems.\n-Data structures and algorithms: Students learn how to represent and manipulate data efficiently using structures such as arrays, lists, stacks, queues, and trees, and how to design and analyze algorithms for searching, sorting, and graph traversal.\n-Software engineering principles: Students learn how to apply principles of software engineering, such as design patterns, testing, and version control, to build maintainable and scalable software systems.\n-Computer organization and architecture: Students learn how computers work at a low level, including topics such as digital logic, instruction set architecture, and memory hierarchy.\n-Operating systems: Students learn about the design and implementation of operating systems, including topics such as process management, memory management, and file systems.\n-Databases: Students learn how to design and use databases to store, manipulate, and retrieve data using query languages such as SQL and to work with different database management systems such as MySQL and Oracle.\n-Computer networks: Students learn how to design and manage computer networks, including topics such as TCP/IP, routing, and network security.\n-Artificial intelligence: Students learn about the principles and applications of artificial intelligence, including machine learning, natural language processing, and computer vision.\n-Mathematics: Students learn mathematical concepts and methods that are foundational to computer science, such as discrete mathematics, calculus, and linear algebra.\n-Web development: Students learn how to design and develop web applications using languages and tools such as HTML, CSS, JavaScript, and web frameworks such as Django and Ruby on Rails."])</script><script>self.__next_f.push([1,"3e8:Ta37,"])</script><script>self.__next_f.push([1,"UMass Boston, located in America’s most celebrated college city, combines the resources of a major research university and the accessibility of a public institution. With 65+ courses of study and a prestigious Honors College, UMass Boston gives you access to career opportunities, research projects, and a strong alumni network. With 11% of the student body representing 140+ countries and speaking 60+ languages, UMass Boston is truly global.\n-In an undergraduate computer science degree, students learn programming, software engineering, computer organization, databases, computer networks, artificial intelligence, and mathematics. The program includes lectures, lab work, and projects.\n-Programming languages: Students learn to write code in various programming languages, such as Java, Python, and C++, and to apply programming constructs such as loops, functions, and conditionals to solve problems.\n-Data structures and algorithms: Students learn how to represent and manipulate data efficiently using structures such as arrays, lists, stacks, queues, and trees, and how to design and analyze algorithms for searching, sorting, and graph traversal.\n-Software engineering principles: Students learn how to apply principles of software engineering, such as design patterns, testing, and version control, to build maintainable and scalable software systems.\n-Computer organization and architecture: Students learn how computers work at a low level, including topics such as digital logic, instruction set architecture, and memory hierarchy.\n-Operating systems: Students learn about the design and implementation of operating systems, including topics such as process management, memory management, and file systems.\n-Databases: Students learn how to design and use databases to store, manipulate, and retrieve data using query languages such as SQL and to work with different database management systems such as MySQL and Oracle.\n-Computer networks: Students learn how to design and manage computer networks, including topics such as TCP/IP, routing, and network security.\n-Artificial intelligence: Students learn about the principles and applications of artificial intelligence, including machine learning, natural language processing, and computer vision.\n-Mathematics: Students learn mathematical concepts and methods that are foundational to computer science, such as discrete mathematics, calculus, and linear algebra.\n-Web development: Students learn how to design and develop web applications using languages and tools such as HTML, CSS, JavaScript, and web frameworks such as Django and Ruby on Rails."])</script><script>self.__next_f.push([1,"3e9:Ta33,"])</script><script>self.__next_f.push([1,"The University of Utah is located on a picturesque campus in Salt Lake City. Utah creates global leaders by placing a strong emphasis on entrepreneurship, innovation, and quality of life. The Utah College of Engineering - ranked #61 in Undergraduate Engineering by U.S. News \u0026 World Report (2020) - prepares students to improve the productivity, health, safety, and enjoyment of human life through leading-edge research and tech development.\n-In an undergraduate computer science degree, students learn programming, software engineering, computer organization, databases, computer networks, artificial intelligence, and mathematics. The program includes lectures, lab work, and projects.\n-Programming languages: Students learn to write code in various programming languages, such as Java, Python, and C++, and to apply programming constructs such as loops, functions, and conditionals to solve problems.\n-Data structures and algorithms: Students learn how to represent and manipulate data efficiently using structures such as arrays, lists, stacks, queues, and trees, and how to design and analyze algorithms for searching, sorting, and graph traversal.\n-Software engineering principles: Students learn how to apply principles of software engineering, such as design patterns, testing, and version control, to build maintainable and scalable software systems.\n-Computer organization and architecture: Students learn how computers work at a low level, including topics such as digital logic, instruction set architecture, and memory hierarchy.\n-Operating systems: Students learn about the design and implementation of operating systems, including topics such as process management, memory management, and file systems.\n-Databases: Students learn how to design and use databases to store, manipulate, and retrieve data using query languages such as SQL and to work with different database management systems such as MySQL and Oracle.\n-Computer networks: Students learn how to design and manage computer networks, including topics such as TCP/IP, routing, and network security.\n-Artificial intelligence: Students learn about the principles and applications of artificial intelligence, including machine learning, natural language processing, and computer vision.\n-Mathematics: Students learn mathematical concepts and methods that are foundational to computer science, such as discrete mathematics, calculus, and linear algebra.\n-Web development: Students learn how to design and develop web applications using languages and tools such as HTML, CSS, JavaScript, and web frameworks such as Django and Ruby on Rails."])</script><script>self.__next_f.push([1,"3ea:T945,"])</script><script>self.__next_f.push([1,"- #78 National Universities - U.S. News \u0026 World Report, 2019\n- #5 Best U.S. Cities for Jobs - Fortune, 2018\n- Create meaningful change in America’s vibrant political, historical \u0026 cultural capital city\n-In an undergraduate computer science degree, students learn programming, software engineering, computer organization, databases, computer networks, artificial intelligence, and mathematics. The program includes lectures, lab work, and projects.\n-Programming languages: Students learn to write code in various programming languages, such as Java, Python, and C++, and to apply programming constructs such as loops, functions, and conditionals to solve problems.\n-Data structures and algorithms: Students learn how to represent and manipulate data efficiently using structures such as arrays, lists, stacks, queues, and trees, and how to design and analyze algorithms for searching, sorting, and graph traversal.\n-Software engineering principles: Students learn how to apply principles of software engineering, such as design patterns, testing, and version control, to build maintainable and scalable software systems.\n-Computer organization and architecture: Students learn how computers work at a low level, including topics such as digital logic, instruction set architecture, and memory hierarchy.\n-Operating systems: Students learn about the design and implementation of operating systems, including topics such as process management, memory management, and file systems.\n-Databases: Students learn how to design and use databases to store, manipulate, and retrieve data using query languages such as SQL and to work with different database management systems such as MySQL and Oracle.\n-Computer networks: Students learn how to design and manage computer networks, including topics such as TCP/IP, routing, and network security.\n-Artificial intelligence: Students learn about the principles and applications of artificial intelligence, including machine learning, natural language processing, and computer vision.\n-Mathematics: Students learn mathematical concepts and methods that are foundational to computer science, such as discrete mathematics, calculus, and linear algebra.\n-Web development: Students learn how to design and develop web applications using languages and tools such as HTML, CSS, JavaScript, and web frameworks such as Django and Ruby on Rails."])</script><script>self.__next_f.push([1,"3eb:T9d2,"])</script><script>self.__next_f.push([1,"Cleveland State University partners with world-class hospitals, Fortune 500 companies, government research centers, and cultural institutions to give its students academic, research, and job opportunities. With more than 175+ undergraduate degrees to choose from, Cleveland State Global students are prepared to succeed in the global workforce.\n-In an undergraduate computer science degree, students learn programming, software engineering, computer organization, databases, computer networks, artificial intelligence, and mathematics. The program includes lectures, lab work, and projects.\n-Programming languages: Students learn to write code in various programming languages, such as Java, Python, and C++, and to apply programming constructs such as loops, functions, and conditionals to solve problems.\n-Data structures and algorithms: Students learn how to represent and manipulate data efficiently using structures such as arrays, lists, stacks, queues, and trees, and how to design and analyze algorithms for searching, sorting, and graph traversal.\n-Software engineering principles: Students learn how to apply principles of software engineering, such as design patterns, testing, and version control, to build maintainable and scalable software systems.\n-Computer organization and architecture: Students learn how computers work at a low level, including topics such as digital logic, instruction set architecture, and memory hierarchy.\n-Operating systems: Students learn about the design and implementation of operating systems, including topics such as process management, memory management, and file systems.\n-Databases: Students learn how to design and use databases to store, manipulate, and retrieve data using query languages such as SQL and to work with different database management systems such as MySQL and Oracle.\n-Computer networks: Students learn how to design and manage computer networks, including topics such as TCP/IP, routing, and network security.\n-Artificial intelligence: Students learn about the principles and applications of artificial intelligence, including machine learning, natural language processing, and computer vision.\n-Mathematics: Students learn mathematical concepts and methods that are foundational to computer science, such as discrete mathematics, calculus, and linear algebra.\n-Web development: Students learn how to design and develop web applications using languages and tools such as HTML, CSS, JavaScript, and web frameworks such as Django and Ruby on Rails."])</script><script>self.__next_f.push([1,"3ec:Ta13,"])</script><script>self.__next_f.push([1,"The University of Dayton is a top-tier research university dedicated to academic excellence, community leadership, entrepreneurship, and creating a positive global impact. University of Dayton offers international students 80+ undergraduate degree options. The University of Dayton’s popular and highly ranked programs include engineering, entrepreneurship, business, and aerospace and aviation engineering.\n-In an undergraduate computer science degree, students learn programming, software engineering, computer organization, databases, computer networks, artificial intelligence, and mathematics. The program includes lectures, lab work, and projects.\n-Programming languages: Students learn to write code in various programming languages, such as Java, Python, and C++, and to apply programming constructs such as loops, functions, and conditionals to solve problems.\n-Data structures and algorithms: Students learn how to represent and manipulate data efficiently using structures such as arrays, lists, stacks, queues, and trees, and how to design and analyze algorithms for searching, sorting, and graph traversal.\n-Software engineering principles: Students learn how to apply principles of software engineering, such as design patterns, testing, and version control, to build maintainable and scalable software systems.\n-Computer organization and architecture: Students learn how computers work at a low level, including topics such as digital logic, instruction set architecture, and memory hierarchy.\n-Operating systems: Students learn about the design and implementation of operating systems, including topics such as process management, memory management, and file systems.\n-Databases: Students learn how to design and use databases to store, manipulate, and retrieve data using query languages such as SQL and to work with different database management systems such as MySQL and Oracle.\n-Computer networks: Students learn how to design and manage computer networks, including topics such as TCP/IP, routing, and network security.\n-Artificial intelligence: Students learn about the principles and applications of artificial intelligence, including machine learning, natural language processing, and computer vision.\n-Mathematics: Students learn mathematical concepts and methods that are foundational to computer science, such as discrete mathematics, calculus, and linear algebra.\n-Web development: Students learn how to design and develop web applications using languages and tools such as HTML, CSS, JavaScript, and web frameworks such as Django and Ruby on Rails."])</script><script>self.__next_f.push([1,"3ed:T9ea,"])</script><script>self.__next_f.push([1,"Florida International University is one of the largest public research universities in the US. The FIU Global First Year program prepares you for academic, social, and professional success. Florida International University offers 110+ undergraduate programs. International business, hospitality, engineering, and criminal justice are among FIU’s top fields of study.\n-In an undergraduate computer science degree, students learn programming, software engineering, computer organization, databases, computer networks, artificial intelligence, and mathematics. The program includes lectures, lab work, and projects.\n-Programming languages: Students learn to write code in various programming languages, such as Java, Python, and C++, and to apply programming constructs such as loops, functions, and conditionals to solve problems.\n-Data structures and algorithms: Students learn how to represent and manipulate data efficiently using structures such as arrays, lists, stacks, queues, and trees, and how to design and analyze algorithms for searching, sorting, and graph traversal.\n-Software engineering principles: Students learn how to apply principles of software engineering, such as design patterns, testing, and version control, to build maintainable and scalable software systems.\n-Computer organization and architecture: Students learn how computers work at a low level, including topics such as digital logic, instruction set architecture, and memory hierarchy.\n-Operating systems: Students learn about the design and implementation of operating systems, including topics such as process management, memory management, and file systems.\n-Databases: Students learn how to design and use databases to store, manipulate, and retrieve data using query languages such as SQL and to work with different database management systems such as MySQL and Oracle.\n-Computer networks: Students learn how to design and manage computer networks, including topics such as TCP/IP, routing, and network security.\n-Artificial intelligence: Students learn about the principles and applications of artificial intelligence, including machine learning, natural language processing, and computer vision.\n-Mathematics: Students learn mathematical concepts and methods that are foundational to computer science, such as discrete mathematics, calculus, and linear algebra.\n-Web development: Students learn how to design and develop web applications using languages and tools such as HTML, CSS, JavaScript, and web frameworks such as Django and Ruby on Rails."])</script><script>self.__next_f.push([1,"3ee:T9b2,"])</script><script>self.__next_f.push([1,"University of the Pacific's undergraduate programs are offered at the Stockton, California campus and offer world-class instruction in a supportive and challenging atmosphere. University of the Pacific offers 80+ undergraduate majors, small class sizes, a diverse campus experience, and internship opportunities.\n-In an undergraduate computer science degree, students learn programming, software engineering, computer organization, databases, computer networks, artificial intelligence, and mathematics. The program includes lectures, lab work, and projects.\n-Programming languages: Students learn to write code in various programming languages, such as Java, Python, and C++, and to apply programming constructs such as loops, functions, and conditionals to solve problems.\n-Data structures and algorithms: Students learn how to represent and manipulate data efficiently using structures such as arrays, lists, stacks, queues, and trees, and how to design and analyze algorithms for searching, sorting, and graph traversal.\n-Software engineering principles: Students learn how to apply principles of software engineering, such as design patterns, testing, and version control, to build maintainable and scalable software systems.\n-Computer organization and architecture: Students learn how computers work at a low level, including topics such as digital logic, instruction set architecture, and memory hierarchy.\n-Operating systems: Students learn about the design and implementation of operating systems, including topics such as process management, memory management, and file systems.\n-Databases: Students learn how to design and use databases to store, manipulate, and retrieve data using query languages such as SQL and to work with different database management systems such as MySQL and Oracle.\n-Computer networks: Students learn how to design and manage computer networks, including topics such as TCP/IP, routing, and network security.\n-Artificial intelligence: Students learn about the principles and applications of artificial intelligence, including machine learning, natural language processing, and computer vision.\n-Mathematics: Students learn mathematical concepts and methods that are foundational to computer science, such as discrete mathematics, calculus, and linear algebra.\n-Web development: Students learn how to design and develop web applications using languages and tools such as HTML, CSS, JavaScript, and web frameworks such as Django and Ruby on Rails."])</script><script>self.__next_f.push([1,"3ef:T707,UMass Boston, located in America’s most celebrated college city, combines the resources of a major research university and the accessibility of a public institution. With 65+ courses of study and a prestigious Honors College, UMass Boston gives you access to career opportunities, research projects, and a strong alumni network. With 11% of the student body representing 140+ countries and speaking 60+ languages, UMass Boston is truly global.\n-An undergraduate degree in Mathematics teaches students the principles of pure and applied mathematics, including calculus, algebra, and analysis.\n-Students learn about mathematical proof and how to construct rigorous and logical arguments.\n-They study the foundations of geometry, topology, and number theory.\n-Mathematics students develop problem-solving skills, critical thinking, and logical reasoning that are useful in a wide range of fields.\n-They learn about the applications of mathematics in fields such as physics, engineering, finance, and computer science.\n-Students study the principles of probability theory and statistics, including methods of statistical inference and data analysis.\n-Mathematics students learn how to use mathematical software and computer programming languages to solve mathematical problems and simulate real-world scenarios.\n-They also study the history and philosophy of mathematics, exploring the development of mathematical ideas and their relationship to other fields of study.\n-Mathematics students learn how to communicate mathematical ideas and findings through technical writing and presentations.\n-Finally, an undergraduate degree in Mathematics prepares students for careers in various fields such as academia, industry, and government, as well as for further study in graduate and professional programs.3f0:T7c3,The University of South Carolina is a globally recognized, high-impact research university committed to a superior student experience and dedicated to innovation in learning, research, and community engagement. UofSC offers 350+ de"])</script><script>self.__next_f.push([1,"gree programs and is one of only 40 public universities to receive Carnegie Classifications for both top-tier research activity and community engagement.\n-An undergraduate degree in Information Science teaches students how to organize, manage, and analyze large amounts of data, using tools and techniques such as databases, data mining, and machine learning.\n-They learn the fundamentals of computer science and programming, including algorithms, data structures, and software development.\n-Students learn about user experience (UX) and user interface (UI) design principles to develop applications that are easy to use and navigate.\n-They also study the principles of human-computer interaction (HCI), understanding how humans interact with technology and how to design technology that is both useful and usable.\n-Information science students learn about the legal and ethical issues surrounding information and data management, such as privacy, intellectual property, and data security.\n-They study the use of information technology in organizations, including the design and management of information systems that support business processes and decision-making.\n-Students learn about data visualization, exploring ways to present complex data and information in visual formats that are easy to understand.\n-They also learn about information retrieval, including search engines and the algorithms that underpin them.\n-An undergraduate degree in Information Science teaches students how to work collaboratively in teams and communicate technical information to non-technical stakeholders.\n-Finally, students learn about emerging technologies and their potential impact on society, preparing them to be innovative and responsible technology professionals.3f1:T85d,"])</script><script>self.__next_f.push([1,"Western New England University offers a hands-on and personalized educational experience, with small class sizes and nurturing faculty. The 215-acre campus offers a vibrant community where students can explore cutting-edge research, entrepreneurial prospects, and creative pursuits, all while building a wide professional network. With degree programs in high-demand fields such as engineering, health, pharmaceuticals, and business, Western New England University prepares students to get started on their career journey. Learn from industry professionals as you develop key skills and gain in-depth knowledge that will help you stand out to employers in the US, or anywhere in the world.\n-An undergraduate degree in Mathematical Sciences teaches students the principles of pure and applied mathematics, including calculus, algebra, and analysis.\n-Students learn about the use of mathematical models to solve real-world problems in fields such as engineering, physics, and finance.\n-They study probability theory and statistics, including methods of statistical inference and data analysis.\n-Mathematical Sciences students learn about the foundations of computer science, including algorithms, programming, and data structures.\n-They also study the principles of mathematical logic and the foundations of mathematics, including set theory and topology.\n-Students develop skills in problem-solving, critical thinking, and logical reasoning, which are useful in a wide range of fields.\n-They learn about the use of mathematical software and computer programming languages to solve mathematical problems and simulate real-world scenarios.\n-Mathematical Sciences students study the history and philosophy of mathematics, exploring the development of mathematical ideas and their relationship to other fields of study.\n-They learn how to communicate mathematical ideas and findings through technical writing and presentations.\n-Finally, an undergraduate degree in Mathematical Sciences prepares students for careers in various fields such as academia, industry, and government, as well as for further study in graduate and professional programs."])</script><script>self.__next_f.push([1,"3f2:T636,- #147 National Universities - U.S. News \u0026 World Report, 2019\n- A true campus experience just minutes from the cultural and financial capital of the world\n- 240+ major companies recruit on campus Apple, IBM, AIG, Pepsi and Merrill Lynch\n-An undergraduate degree in Mathematics teaches students the principles of pure and applied mathematics, including calculus, algebra, and analysis.\n-Students learn about mathematical proof and how to construct rigorous and logical arguments.\n-They study the foundations of geometry, topology, and number theory.\n-Mathematics students develop problem-solving skills, critical thinking, and logical reasoning that are useful in a wide range of fields.\n-They learn about the applications of mathematics in fields such as physics, engineering, finance, and computer science.\n-Students study the principles of probability theory and statistics, including methods of statistical inference and data analysis.\n-Mathematics students learn how to use mathematical software and computer programming languages to solve mathematical problems and simulate real-world scenarios.\n-They also study the history and philosophy of mathematics, exploring the development of mathematical ideas and their relationship to other fields of study.\n-Mathematics students learn how to communicate mathematical ideas and findings through technical writing and presentations.\n-Finally, an undergraduate degree in Mathematics prepares students for careers in various fields such as academia, industry, and government, as well as for further study in graduate and professional programs.3f3:T6d8,Louisiana State University is a Top 100 Public University with a dedicated focus on student involvement, research opportunities, and experiential learning. With more than 330 fields of study and 70 majors, LSU offers students opportunities for hands-on experience working alongside world-class faculty. Top-ranked and popular programs include business, engineering, petroleum engineering, and STEM.\n-An undergraduate degree in Mathematics t"])</script><script>self.__next_f.push([1,"eaches students the principles of pure and applied mathematics, including calculus, algebra, and analysis.\n-Students learn about mathematical proof and how to construct rigorous and logical arguments.\n-They study the foundations of geometry, topology, and number theory.\n-Mathematics students develop problem-solving skills, critical thinking, and logical reasoning that are useful in a wide range of fields.\n-They learn about the applications of mathematics in fields such as physics, engineering, finance, and computer science.\n-Students study the principles of probability theory and statistics, including methods of statistical inference and data analysis.\n-Mathematics students learn how to use mathematical software and computer programming languages to solve mathematical problems and simulate real-world scenarios.\n-They also study the history and philosophy of mathematics, exploring the development of mathematical ideas and their relationship to other fields of study.\n-Mathematics students learn how to communicate mathematical ideas and findings through technical writing and presentations.\n-Finally, an undergraduate degree in Mathematics prepares students for careers in various fields such as academia, industry, and government, as well as for further study in graduate and professional programs.3f4:T6a9,Auburn University prepares you for success with its prestigious academic programs, emphasis on hands-on learning experiences, and family spirit. Auburn University offers more than 150 undergraduate degrees, including top-ranked programs in engineering, business, supply chain management, journalism, architecture and design, and fisheries/aquaculture.\n-An undergraduate degree in Mathematics teaches students the principles of pure and applied mathematics, including calculus, algebra, and analysis.\n-Students learn about mathematical proof and how to construct rigorous and logical arguments.\n-They study the foundations of geometry, topology, and number theory.\n-Mathematics students develop problem-solving skills, critical "])</script><script>self.__next_f.push([1,"thinking, and logical reasoning that are useful in a wide range of fields.\n-They learn about the applications of mathematics in fields such as physics, engineering, finance, and computer science.\n-Students study the principles of probability theory and statistics, including methods of statistical inference and data analysis.\n-Mathematics students learn how to use mathematical software and computer programming languages to solve mathematical problems and simulate real-world scenarios.\n-They also study the history and philosophy of mathematics, exploring the development of mathematical ideas and their relationship to other fields of study.\n-Mathematics students learn how to communicate mathematical ideas and findings through technical writing and presentations.\n-Finally, an undergraduate degree in Mathematics prepares students for careers in various fields such as academia, industry, and government, as well as for further study in graduate and professional programs.3f5:T6c5,The University of Illinois Chicago provides a hands-on learning experience in a supportive, diverse environment. Located in downtown Chicago, UIC offers you the opportunity to live, learn, and excel in the third-largest city in the US. UIC’s top-ranked programs include engineering, business, architecture, design, education, health sciences, public health, and public affairs.\n-An undergraduate degree in Mathematics teaches students the principles of pure and applied mathematics, including calculus, algebra, and analysis.\n-Students learn about mathematical proof and how to construct rigorous and logical arguments.\n-They study the foundations of geometry, topology, and number theory.\n-Mathematics students develop problem-solving skills, critical thinking, and logical reasoning that are useful in a wide range of fields.\n-They learn about the applications of mathematics in fields such as physics, engineering, finance, and computer science.\n-Students study the principles of probability theory and statistics, including methods of statistical inferenc"])</script><script>self.__next_f.push([1,"e and data analysis.\n-Mathematics students learn how to use mathematical software and computer programming languages to solve mathematical problems and simulate real-world scenarios.\n-They also study the history and philosophy of mathematics, exploring the development of mathematical ideas and their relationship to other fields of study.\n-Mathematics students learn how to communicate mathematical ideas and findings through technical writing and presentations.\n-Finally, an undergraduate degree in Mathematics prepares students for careers in various fields such as academia, industry, and government, as well as for further study in graduate and professional programs.3f6:T66c,The University of Kansas is a top-tier public research university with a commitment to a research-focused academic curriculum and career support. At KU, you can choose from over 190 fields of study, including top-ranked business, engineering, pharmacy, education, and architecture programs.\n-An undergraduate degree in Mathematics teaches students the principles of pure and applied mathematics, including calculus, algebra, and analysis.\n-Students learn about mathematical proof and how to construct rigorous and logical arguments.\n-They study the foundations of geometry, topology, and number theory.\n-Mathematics students develop problem-solving skills, critical thinking, and logical reasoning that are useful in a wide range of fields.\n-They learn about the applications of mathematics in fields such as physics, engineering, finance, and computer science.\n-Students study the principles of probability theory and statistics, including methods of statistical inference and data analysis.\n-Mathematics students learn how to use mathematical software and computer programming languages to solve mathematical problems and simulate real-world scenarios.\n-They also study the history and philosophy of mathematics, exploring the development of mathematical ideas and their relationship to other fields of study.\n-Mathematics students learn how to communicate mathemat"])</script><script>self.__next_f.push([1,"ical ideas and findings through technical writing and presentations.\n-Finally, an undergraduate degree in Mathematics prepares students for careers in various fields such as academia, industry, and government, as well as for further study in graduate and professional programs.3f7:T4a4,I didn’t want theory — I could do theory all day. I wanted something I \r\ncould use immediately when I walk out the door, and that’s what Maryville’s \r\ncourses provided.” — Felecia W., Maryville Grad The digital world runs on \r\ndata. So can your career. We live in a digital world — one in which \r\nexamples of data science and analysis can be found everywhere. Consider \r\nyour product recommendations from Amazon. Think about how companies in \r\ndifferent industries like Boeing, Walmart, and Disney use data to drive \r\ncritical business decisions, and insurance companies depend on this \r\nanalysis to forecast risk or banks to evaluate loan applications. Now \r\nimagine the career potential if you had the skills to help them do it. Earn \r\nyour bachelor’s in data science online from Maryville University, and \r\nyou’ll do more than study the tools and techniques used to dig deeper into \r\ndata. Graduates can build the skills to explore, analyze, monitor, manage, \r\nand visualize large data sets using the latest technology. Our innovative \r\nprogram also features a business minor, which can help prepare you for top \r\ndata jobs in nearly any field. Get Curriculum Details3f8:T855,"])</script><script>self.__next_f.push([1,"The University of Illinois Chicago provides a hands-on learning experience in a supportive, diverse environment. Located in downtown Chicago, UIC offers you the opportunity to live, learn, and excel in the third-largest city in the US. UIC’s top-ranked programs include engineering, business, architecture, design, education, health sciences, public health, and public affairs.\n-An undergraduate Engineering degree teaches students the fundamental principles of science and mathematics and how to design, analyze, and improve various engineering systems. The curriculum includes courses in physics, calculus, chemistry, engineering design, materials science, mechanics, thermodynamics, electronics, and control systems. \n-An undergraduate engineering degree teaches students the principles of mathematics, physics, and materials science that are used to design and build machines, structures, and systems.\n-Students learn how to use software tools and computer-aided design (CAD) software to create 2D and 3D models of parts and assemblies.\n-They also learn how to select and use appropriate manufacturing methods to produce parts and assemblies.\n-Engineering students study thermodynamics, fluid mechanics, and heat transfer to understand the behavior of fluids and gases in systems such as engines and turbines.\n-They learn the principles of electrical and electronic circuits and how to use them to design and analyze circuits and systems.\n-Materials science is an important part of an engineering degree, with students learning about the properties and behavior of different materials under different conditions.\n-Engineering students also learn about the principles of control systems and how to design and analyze feedback systems.\n-They learn about the principles of mechanics and how to apply them to design and analyze structures such as buildings and bridges.\n-An undergraduate engineering degree also teaches students about project management and the skills needed to work effectively in teams.\n-Finally, engineering students learn how to communicate their ideas and findings through technical writing and presentations."])</script><script>self.__next_f.push([1,"3f9:T7fc,The University of Kansas is a top-tier public research university with a commitment to a research-focused academic curriculum and career support. At KU, you can choose from over 190 fields of study, including top-ranked business, engineering, pharmacy, education, and architecture programs.\n-An undergraduate Engineering degree teaches students the fundamental principles of science and mathematics and how to design, analyze, and improve various engineering systems. The curriculum includes courses in physics, calculus, chemistry, engineering design, materials science, mechanics, thermodynamics, electronics, and control systems. \n-An undergraduate engineering degree teaches students the principles of mathematics, physics, and materials science that are used to design and build machines, structures, and systems.\n-Students learn how to use software tools and computer-aided design (CAD) software to create 2D and 3D models of parts and assemblies.\n-They also learn how to select and use appropriate manufacturing methods to produce parts and assemblies.\n-Engineering students study thermodynamics, fluid mechanics, and heat transfer to understand the behavior of fluids and gases in systems such as engines and turbines.\n-They learn the principles of electrical and electronic circuits and how to use them to design and analyze circuits and systems.\n-Materials science is an important part of an engineering degree, with students learning about the properties and behavior of different materials under different conditions.\n-Engineering students also learn about the principles of control systems and how to design and analyze feedback systems.\n-They learn about the principles of mechanics and how to apply them to design and analyze structures such as buildings and bridges.\n-An undergraduate engineering degree also teaches students about project management and the skills needed to work effectively in teams.\n-Finally, engineering students learn how to communicate their ideas and findings through technical writing and presentat"])</script><script>self.__next_f.push([1,"ions.3fa:T897,"])</script><script>self.__next_f.push([1,"UMass Boston, located in America’s most celebrated college city, combines the resources of a major research university and the accessibility of a public institution. With 65+ courses of study and a prestigious Honors College, UMass Boston gives you access to career opportunities, research projects, and a strong alumni network. With 11% of the student body representing 140+ countries and speaking 60+ languages, UMass Boston is truly global.\n-An undergraduate Engineering degree teaches students the fundamental principles of science and mathematics and how to design, analyze, and improve various engineering systems. The curriculum includes courses in physics, calculus, chemistry, engineering design, materials science, mechanics, thermodynamics, electronics, and control systems. \n-An undergraduate engineering degree teaches students the principles of mathematics, physics, and materials science that are used to design and build machines, structures, and systems.\n-Students learn how to use software tools and computer-aided design (CAD) software to create 2D and 3D models of parts and assemblies.\n-They also learn how to select and use appropriate manufacturing methods to produce parts and assemblies.\n-Engineering students study thermodynamics, fluid mechanics, and heat transfer to understand the behavior of fluids and gases in systems such as engines and turbines.\n-They learn the principles of electrical and electronic circuits and how to use them to design and analyze circuits and systems.\n-Materials science is an important part of an engineering degree, with students learning about the properties and behavior of different materials under different conditions.\n-Engineering students also learn about the principles of control systems and how to design and analyze feedback systems.\n-They learn about the principles of mechanics and how to apply them to design and analyze structures such as buildings and bridges.\n-An undergraduate engineering degree also teaches students about project management and the skills needed to work effectively in teams.\n-Finally, engineering students learn how to communicate their ideas and findings through technical writing and presentations."])</script><script>self.__next_f.push([1,"3fb:T83a,"])</script><script>self.__next_f.push([1,"Auburn University prepares you for success with its prestigious academic programs, emphasis on hands-on learning experiences, and family spirit. Auburn University offers more than 150 undergraduate degrees, including top-ranked programs in engineering, business, supply chain management, journalism, architecture and design, and fisheries/aquaculture.\n-An undergraduate Engineering degree teaches students the fundamental principles of science and mathematics and how to design, analyze, and improve various engineering systems. The curriculum includes courses in physics, calculus, chemistry, engineering design, materials science, mechanics, thermodynamics, electronics, and control systems. \n-An undergraduate engineering degree teaches students the principles of mathematics, physics, and materials science that are used to design and build machines, structures, and systems.\n-Students learn how to use software tools and computer-aided design (CAD) software to create 2D and 3D models of parts and assemblies.\n-They also learn how to select and use appropriate manufacturing methods to produce parts and assemblies.\n-Engineering students study thermodynamics, fluid mechanics, and heat transfer to understand the behavior of fluids and gases in systems such as engines and turbines.\n-They learn the principles of electrical and electronic circuits and how to use them to design and analyze circuits and systems.\n-Materials science is an important part of an engineering degree, with students learning about the properties and behavior of different materials under different conditions.\n-Engineering students also learn about the principles of control systems and how to design and analyze feedback systems.\n-They learn about the principles of mechanics and how to apply them to design and analyze structures such as buildings and bridges.\n-An undergraduate engineering degree also teaches students about project management and the skills needed to work effectively in teams.\n-Finally, engineering students learn how to communicate their ideas and findings through technical writing and presentations.\n"])</script><script>self.__next_f.push([1,"3fc:T812,"])</script><script>self.__next_f.push([1,"University of the Pacific's undergraduate programs are offered at the Stockton, California campus and offer world-class instruction in a supportive and challenging atmosphere. University of the Pacific offers 80+ undergraduate majors, small class sizes, a diverse campus experience, and internship opportunities.\n-An undergraduate Engineering degree teaches students the fundamental principles of science and mathematics and how to design, analyze, and improve various engineering systems. The curriculum includes courses in physics, calculus, chemistry, engineering design, materials science, mechanics, thermodynamics, electronics, and control systems. \n-An undergraduate engineering degree teaches students the principles of mathematics, physics, and materials science that are used to design and build machines, structures, and systems.\n-Students learn how to use software tools and computer-aided design (CAD) software to create 2D and 3D models of parts and assemblies.\n-They also learn how to select and use appropriate manufacturing methods to produce parts and assemblies.\n-Engineering students study thermodynamics, fluid mechanics, and heat transfer to understand the behavior of fluids and gases in systems such as engines and turbines.\n-They learn the principles of electrical and electronic circuits and how to use them to design and analyze circuits and systems.\n-Materials science is an important part of an engineering degree, with students learning about the properties and behavior of different materials under different conditions.\n-Engineering students also learn about the principles of control systems and how to design and analyze feedback systems.\n-They learn about the principles of mechanics and how to apply them to design and analyze structures such as buildings and bridges.\n-An undergraduate engineering degree also teaches students about project management and the skills needed to work effectively in teams.\n-Finally, engineering students learn how to communicate their ideas and findings through technical writing and presentations."])</script><script>self.__next_f.push([1,"3fd:T84a,"])</script><script>self.__next_f.push([1,"Florida International University is one of the largest public research universities in the US. The FIU Global First Year program prepares you for academic, social, and professional success. Florida International University offers 110+ undergraduate programs. International business, hospitality, engineering, and criminal justice are among FIU’s top fields of study.\n-An undergraduate Engineering degree teaches students the fundamental principles of science and mathematics and how to design, analyze, and improve various engineering systems. The curriculum includes courses in physics, calculus, chemistry, engineering design, materials science, mechanics, thermodynamics, electronics, and control systems. \n-An undergraduate engineering degree teaches students the principles of mathematics, physics, and materials science that are used to design and build machines, structures, and systems.\n-Students learn how to use software tools and computer-aided design (CAD) software to create 2D and 3D models of parts and assemblies.\n-They also learn how to select and use appropriate manufacturing methods to produce parts and assemblies.\n-Engineering students study thermodynamics, fluid mechanics, and heat transfer to understand the behavior of fluids and gases in systems such as engines and turbines.\n-They learn the principles of electrical and electronic circuits and how to use them to design and analyze circuits and systems.\n-Materials science is an important part of an engineering degree, with students learning about the properties and behavior of different materials under different conditions.\n-Engineering students also learn about the principles of control systems and how to design and analyze feedback systems.\n-They learn about the principles of mechanics and how to apply them to design and analyze structures such as buildings and bridges.\n-An undergraduate engineering degree also teaches students about project management and the skills needed to work effectively in teams.\n-Finally, engineering students learn how to communicate their ideas and findings through technical writing and presentations."])</script><script>self.__next_f.push([1,"3fe:T873,"])</script><script>self.__next_f.push([1,"The University of Dayton is a top-tier research university dedicated to academic excellence, community leadership, entrepreneurship, and creating a positive global impact. University of Dayton offers international students 80+ undergraduate degree options. The University of Dayton’s popular and highly ranked programs include engineering, entrepreneurship, business, and aerospace and aviation engineering.\n-An undergraduate Engineering degree teaches students the fundamental principles of science and mathematics and how to design, analyze, and improve various engineering systems. The curriculum includes courses in physics, calculus, chemistry, engineering design, materials science, mechanics, thermodynamics, electronics, and control systems. \n-An undergraduate engineering degree teaches students the principles of mathematics, physics, and materials science that are used to design and build machines, structures, and systems.\n-Students learn how to use software tools and computer-aided design (CAD) software to create 2D and 3D models of parts and assemblies.\n-They also learn how to select and use appropriate manufacturing methods to produce parts and assemblies.\n-Engineering students study thermodynamics, fluid mechanics, and heat transfer to understand the behavior of fluids and gases in systems such as engines and turbines.\n-They learn the principles of electrical and electronic circuits and how to use them to design and analyze circuits and systems.\n-Materials science is an important part of an engineering degree, with students learning about the properties and behavior of different materials under different conditions.\n-Engineering students also learn about the principles of control systems and how to design and analyze feedback systems.\n-They learn about the principles of mechanics and how to apply them to design and analyze structures such as buildings and bridges.\n-An undergraduate engineering degree also teaches students about project management and the skills needed to work effectively in teams.\n-Finally, engineering students learn how to communicate their ideas and findings through technical writing and presentations."])</script><script>self.__next_f.push([1,"3ff:T7ae,Florida International University is one of the largest public research universities in the US. The FIU Global First Year program prepares you for academic, social, and professional success. Florida International University offers 110+ undergraduate programs. International business, hospitality, engineering, and criminal justice are among FIU’s top fields of study.\n-An undergraduate degree in Mathematics and Statistics teaches students the principles of pure and applied mathematics, including calculus, algebra, and analysis, as well as statistical theory and methods.\n-Students learn about mathematical proof and how to construct rigorous and logical arguments.\n-They study the foundations of probability theory and statistics, including methods of statistical inference and data analysis.\n-Mathematics and Statistics students develop problem-solving skills, critical thinking, and logical reasoning that are useful in a wide range of fields.\n-They learn about the applications of mathematics and statistics in fields such as physics, engineering, finance, and data science.\n-Students study the principles of mathematical modeling and simulation, using mathematical and statistical tools to solve real-world problems.\n-Mathematics and Statistics students learn how to use mathematical and statistical software and computer programming languages to solve mathematical and statistical problems.\n-They also study the history and philosophy of mathematics and statistics, exploring the development of mathematical and statistical ideas and their relationship to other fields of study.\n-Mathematics and Statistics students learn how to communicate mathematical and statistical ideas and findings through technical writing and presentations.\n-Finally, an undergraduate degree in Mathematics and Statistics prepares students for careers in various fields such as academia, industry, and government, as well as for further study in graduate and professional programs.400:T893,"])</script><script>self.__next_f.push([1,"The University of Utah is located on a picturesque campus in Salt Lake City. Utah creates global leaders by placing a strong emphasis on entrepreneurship, innovation, and quality of life. The Utah College of Engineering - ranked #61 in Undergraduate Engineering by U.S. News \u0026 World Report (2020) - prepares students to improve the productivity, health, safety, and enjoyment of human life through leading-edge research and tech development.\n-An undergraduate Engineering degree teaches students the fundamental principles of science and mathematics and how to design, analyze, and improve various engineering systems. The curriculum includes courses in physics, calculus, chemistry, engineering design, materials science, mechanics, thermodynamics, electronics, and control systems. \n-An undergraduate engineering degree teaches students the principles of mathematics, physics, and materials science that are used to design and build machines, structures, and systems.\n-Students learn how to use software tools and computer-aided design (CAD) software to create 2D and 3D models of parts and assemblies.\n-They also learn how to select and use appropriate manufacturing methods to produce parts and assemblies.\n-Engineering students study thermodynamics, fluid mechanics, and heat transfer to understand the behavior of fluids and gases in systems such as engines and turbines.\n-They learn the principles of electrical and electronic circuits and how to use them to design and analyze circuits and systems.\n-Materials science is an important part of an engineering degree, with students learning about the properties and behavior of different materials under different conditions.\n-Engineering students also learn about the principles of control systems and how to design and analyze feedback systems.\n-They learn about the principles of mechanics and how to apply them to design and analyze structures such as buildings and bridges.\n-An undergraduate engineering degree also teaches students about project management and the skills needed to work effectively in teams.\n-Finally, engineering students learn how to communicate their ideas and findings through technical writing and presentations."])</script><script>self.__next_f.push([1,"401:T85a,"])</script><script>self.__next_f.push([1,"The University of South Carolina is a globally recognized, high-impact research university committed to a superior student experience and dedicated to innovation in learning, research, and community engagement. UofSC offers 350+ degree programs and is one of only 40 public universities to receive Carnegie Classifications for both top-tier research activity and community engagement.\n-An undergraduate Engineering degree teaches students the fundamental principles of science and mathematics and how to design, analyze, and improve various engineering systems. 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