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class="no-underline flex items-center"><img alt="CS50's Introduction to Computer Science" title="CS50's Introduction to Computer Science" 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%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" 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class="inline-flex items-center gap-1.5 Breadcrumbs_breadcrumbs__0fm1_ text-primary-foreground capitalize" aria-current="page"><span class="">computer programming</span></li></ol></nav><h1 class="text-learn-hero-heading lg:text-learn-hero-heading-large lg:leading-learn-hero-line-height-large mb-6 font-extrabold tracking-tight">Explore computer programming courses and programs</h1><div class="break-words [&>ul>li>p]:text-white [&>*]:text-white text-xl line-clamp-2"><p class="mb-8">Build essential coding skills needed for front-end and back-end web development, machine learning, iOS and Android app development, and much more. 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These written instructions are often called “code,” as they are written in one of several special programming languages which the computer can understand. Those who can write instructions in one of these codes are called coders, or programmers. </p><p>A programmer’s tasks include understanding project requirements, determining the right programming language to use, designing the solution, coding it, testing and debugging the code, and finally writing documentation that allows their solution to be easily understood by other programmers.</p><p>Computer programming is at the heart of computer science and is the implementation portion of software development, application development, and software engineering efforts. It transforms ideas and theories into working solutions.</p><p>Basic computer programming involves analyzing a problem and developing a logical sequence of instructions to solve it. There can be numerous paths to a solution, but some are much faster than others. 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(1)</button><button type="button" role="tab" aria-selected="false" aria-controls="radix-:R1cjjttrkva:-content-Masters" data-state="inactive" id="radix-:R1cjjttrkva:-trigger-Masters" class="hover:bg-card-gray-hover inline-flex grow items-center justify-center whitespace-nowrap p-3 ring-offset-background 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="">Master's Programs (6)</button><button type="button" role="tab" aria-selected="false" aria-controls="radix-:R1cjjttrkva:-content-Bachelors" data-state="inactive" id="radix-:R1cjjttrkva:-trigger-Bachelors" class="hover:bg-card-gray-hover inline-flex grow items-center justify-center whitespace-nowrap p-3 ring-offset-background 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 (32)</button></div></div><div class="lg:hidden"><button type="button" role="combobox" aria-controls="radix-:Rtcjjttrkva:" aria-expanded="false" aria-autocomplete="none" dir="ltr" data-state="closed" class="h-9 w-full justify-between whitespace-nowrap 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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-:R1cjjttrkva:-trigger-Course" id="radix-:R1cjjttrkva:-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="gap-4 py-4 dynamic-grid flex-wrap undefined"></div></div><div class="lg:hidden"><div class="gap-4 py-4 flex 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-:R1cjjttrkva:-trigger-Executive Education" hidden="" id="radix-:R1cjjttrkva:-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-:R1cjjttrkva:-trigger-Masters" hidden="" id="radix-:R1cjjttrkva:-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-:R1cjjttrkva:-trigger-Bachelors" hidden="" id="radix-:R1cjjttrkva:-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><a class="subnav-item -mt-1" name="Featured Computer Programming Courses" id="featured-computer-programming-courses"></a><div class="flex flex-col gap-2 pb-10"><div class="Default_content__HO8we"><div id=""><h3>Computer programming course curriculum</h3><p>First time codes can begin their educational journey by studying computer programming basics with introductory computer programming classes. These foundational computer programming courses may provide step-by-step tutorials on how to code with a given language. Introductory computer programming training will also explain algorithmic thinking and basic concepts in abstraction, data structures, and resource management.</p><p>You’ll also learn coding languages such as HTML and CSS – two basic languages used for the web. A software development class may teach the “C” family of languages while a data science course would be more likely to focus on Python or SQL. </p><p>Part of learning computer programming is discovering the similarities and differences between different languages while gaining an understanding of which language is the right one for a particular task. Problem sets can be inspired by real-world challenges in fields like biology, finance, and politics.</p></div></div><a class="subnav-item -mt-1" name="Computer programming jobs" id="computer-programming-jobs"></a><div class="Default_content__HO8we"><div id=""><h2>Computer programming jobs</h2><p>People who wish to enter the world of computer programming can choose to specialize in any number of popular programming languages. The type of language you choose and how you implement it may help determine the kind of entry level computer programmer jobs for which you’ll be qualified, and your first job will often guide your career path. However, there is some flexibility when matching jobs with programming languages, and many entry level computer programmer jobs would prefer you to know a handful of the most popular coding languages. </p><p>If you’re interested in becoming a computer programmer or software engineer, it can be valuable to code in as many different languages as you can.</p><p>Some careers in computer programming include:</p><p>● Web developer</p><p>● Computer programmer</p><p>● Software developer</p><p>● Back-end developer</p><p>● Front-end developer</p><p>● Full-stack developer</p><p>● Database administrator</p><p>Take a beginner course in computer science or any number of programming languages and see if this exciting field is right for you. Many introductory, self-paced courses are available to help you learn to code in many different languages. edX offers a variety of learning paths that can fit your needs and schedule, including <span data-boot-camp-link="http://edx.org/boot-camps/">boot camps</span>, online <a class="text-link underline" href="https://edx.org/bachelors/">bachelor’s degree</a> programs, and online <a class="text-link underline" href="http://edx.org/masters/">master's degree</a> programs. </p><h3>How to become a computer programmer online </h3><p>There are many ways to learn computer programming online, but almost all paths require you to start with the basics.<sup><a href="#2deglVNF3aKThyDkya54ln">1</a></sup> A grounding in math and the sciences can benefit you in your coding career. </p><p>First time coders can learn how to code with hands-on <span data-boot-camp-link="http://edx.org/boot-camps/coding">coding boot camp</span>. Learners can then study more advanced concepts by pursuing an online <a class="text-link underline" href="http://edx.org/bachelors/computer-data-sciences">bachelor's in computer science</a> or a <a class="text-link underline" href="https://edx.org/masters/data-science">master's in data science</a>or a similar field. </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 programming FAQ " id="computer-programming-f-a-q"></a><a class="subnav-item" id="frequently-asked-questions"></a><div class="flex flex-col py-4 lg:pt-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-:Rjasjjttrkva:" aria-expanded="false" data-state="closed" data-orientation="vertical" id="radix-:R3asjjttrkva:" class="flex flex-1 gap-10 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=""><span>What is computer programming used for? </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 shrink-0 text-primary-500 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-:Rjasjjttrkva:" hidden="" role="region" aria-labelledby="radix-:R3asjjttrkva:" 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-:Rlasjjttrkva:" aria-expanded="false" data-state="closed" data-orientation="vertical" id="radix-:R5asjjttrkva:" class="flex flex-1 gap-10 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=""><span>What is a computer programming language?</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 shrink-0 text-primary-500 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-:Rlasjjttrkva:" hidden="" role="region" aria-labelledby="radix-:R5asjjttrkva:" 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-:Rnasjjttrkva:" aria-expanded="false" data-state="closed" data-orientation="vertical" id="radix-:R7asjjttrkva:" class="flex flex-1 gap-10 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=""><span>What does a computer programmer do? </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 shrink-0 text-primary-500 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-:Rnasjjttrkva:" hidden="" role="region" aria-labelledby="radix-:R7asjjttrkva:" 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-:Rpasjjttrkva:" aria-expanded="false" data-state="closed" data-orientation="vertical" id="radix-:R9asjjttrkva:" class="flex flex-1 gap-10 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=""><span>How long does it take to learn computer programming? </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 shrink-0 text-primary-500 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-:Rpasjjttrkva:" hidden="" role="region" aria-labelledby="radix-:R9asjjttrkva:" 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-:Rrasjjttrkva:" aria-expanded="false" data-state="closed" data-orientation="vertical" id="radix-:Rbasjjttrkva:" class="flex flex-1 gap-10 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=""><span>Is computer programming hard? </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 shrink-0 text-primary-500 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-:Rrasjjttrkva:" hidden="" role="region" aria-labelledby="radix-:Rbasjjttrkva:" 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-:Rtasjjttrkva:" aria-expanded="false" data-state="closed" data-orientation="vertical" id="radix-:Rdasjjttrkva:" class="flex flex-1 gap-10 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=""><span>How much math is used in computer programming? </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 shrink-0 text-primary-500 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-:Rtasjjttrkva:" hidden="" role="region" aria-labelledby="radix-:Rdasjjttrkva:" 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="2deglVNF3aKThyDkya54ln"><p><a class="text-link underline external" href="https://bootcamp.berkeley.edu/blog/use-these-7-tips-to-help-you-learn-computer-programming-faster/" target="_blank" rel="noopener noreferrer">Use These 7 Tips to Help You Learn Computer Programming Faster</a>. (2020). <i>Berkeley Extension</i>. 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The \"CAAD Internship\" course lasts for one week and is held throughout the week. It is a compulsory internship course for undergraduates majoring in architecture, urban planning, and landscape architecture in the School of Architecture. There are about 120 students. This online course is the first part of the \"CAAD Practical\" course and teaches Grasshopper programming methods. Using the parametric method to design is to intro"])</script><script>self.__next_f.push([1,"duce the thinking of programming into the design and use algorithmic logic to generate geometric shapes. Such a design method can describe the logic of form, function and structure in the design through algorithms, which not only expands the architect's ability to control form, but also makes the design more rational and adaptable. Grasshopper is a widely used parametric design platform. It is based on Rhinoceros three-dimensional modeling software and performs parametric modeling programming based on geometric modeling systems such as Nurbs and Mesh. Grasshopper adopts a graphical programming method. Many common algorithms are encapsulated in modules and combined in a graphical interface. Therefore, it is easy to write and highly efficient, making it very suitable for designers to learn and apply. In addition, Grasshopper, as a parametric design platform, has many plug-ins that can introduce different geometric modeling, physical simulation, and performance optimization algorithms into its system to expand its functions, and these plug-ins are still growing rapidly. Therefore, Grasshopper is a very valuable tool in scheme creation and daily design work, and it is worth learning by every designer.\u003c/p\u003e342: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 p"])</script><script>self.__next_f.push([1,"rogram 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\u003e343: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 may 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\u003e344:T6ae,\u003cp\u003eLinear Algebra: Foundations to Frontiers (LAFF) i"])</script><script>self.__next_f.push([1,"s 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 will 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\u003e345:T643,\u003cp\u003eProbability and inference are used everywhere. For example, they help us figure out which of your emails are spam, what results to show you when you search on Google, how a self-driving car should navigate its environment, or even how a computer can beat the best Jeopardy and Go players! What do all of these examples have in common? They are all situations in which a computer"])</script><script>self.__next_f.push([1," program can carry out inferences in the face of uncertainty at a speed and accuracy that far exceed what we could do in our heads or on a piece of paper.\u003c/p\u003e\n\u003cp\u003eIn this data analysis and computer programming course, you will learn the principles of probability and inference. We will put these mathematical concepts to work in code that solves problems people care about. You will learn about different data structures for storing probability distributions, such as probabilistic graphical models, and build efficient algorithms for reasoning with these data structures.\u003c/p\u003e\n\u003cp\u003eBy the end of this course, you will know how to model real-world problems with probability, and how to use the resulting models for inference.\u003c/p\u003e\n\u003cp\u003eYou don’t need to have prior experience in either probability or inference, but you should be comfortable with basic Python programming and calculus.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e“I love that you can do so much with the material, from programming a robot to move in an unfamiliar environment, to segmenting foreground/background of an image, to classifying tweets on Twitter—all homework examples taken from the class!”\u003c/em\u003e – Previous Student in the residential version of this new online course.\u003c/p\u003e346: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” in"])</script><script>self.__next_f.push([1,"terface.\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\u003e347: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 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;]\"\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\u003e348: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\u003e"])</script><script>self.__next_f.push([1,"This 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\u003e349: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\u003e34a:T63f,\u003cp\u003e“Introduction to Computing in Python”"])</script><script>self.__next_f.push([1," 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 computer 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\u003e34b:T84e,"])</script><script>self.__next_f.push([1,"\u003cp\u003e\u003cimg style=\"max-height:175px\" align=\"right\" alt=\"\" src=\"https://www.edx.org/sites/default/files/edx-prize-logo-2019-winner.png\"/\u003e In this C Programming with Linux Professional Certificate program of seven short courses, you will learn how to write, read and debug computer programs in the C programming language while also becoming familiar with the Linux operating system. \u003c/p\u003e\r\n\r\n\u003cp\u003eBeginners, even those without any programming experience, will be able to immediately start coding in C through our new coding tools within the web browser. No need to install anything! \u003c/p\u003e\r\n\r\n\u003cp\u003eWhy learn C and not another programming language? Did you know that smartphones, your car’s navigation system, robots, drones, trains, and almost all electronic devices have some C-code running under the hood? C is used in any circumstance where speed and flexibility are important, such as in embedded systems or high-performance computing.\u003c/p\u003e\r\n\r\n\u003cp\u003eC is a foundational programming language taught at engineering schools around the world, and represents one of the building blocks of modern computer information technology. Invented in the 1970’s. It is still one of the most stable and popular programming languages in the world.\u003c/p\u003e\r\n\r\n\u003cp\u003eAlong with the C programming language comes Linux, an essential operating system used by most computer scientists and developers. Linux powers almost all supercomputers and most of the servers worldwide as well as all android devices and most internet of things devices. This Professional Certificate Program will introduce the Linux command line and Linux tools for C programmers; both of which are must-have skills in today’s tech industries.\u003c/p\u003e\r\n \r\n\u003cp\u003eYou will practice through guided exercises and short coding demonstrations, as well as more elaborate assignments.\u003c/p\u003e\r\n\r\n\u003cp\u003eOur dedicated international course team is excited to introduce you to the world of coding and guide you along your path to becoming a skilled C programmer and help you pursue a career in computer engineering. \u003c/p\u003e\r\n\r\n\u003cp\u003eThis course has received financial support from the Patrick and Lina Drahi Foundation.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"34c:T734,\u003cp\u003eThis introductory program is designed to give business professionals the basic background on Information Technology (IT) to let them get the most in their interaction with IT professionals, either from their company or from external corporation, as they will have a deeper understanding when identifying requirements, evaluating workloads or supervising results in the IT field.\u003c/p\u003e\r\n\r\n\u003cp\u003eThrough this program, you will learn the basic concepts of information systems and their application, and gain familiarity with the terminology used within the IT field.\u003c/p\u003e\r\n\r\nThis program covers the following topic areas:\r\n\u003cul\u003e\r\n\u003cli\u003e\u003cstrong\u003eInformation Systems and Office Application Software in Organizations:\u003c/strong\u003e\r\nStandard office suite tools, office systems (email, conferencing, etc...), basics of desktop operating systems. Internet, web browsers, Electronic Data Interchange and enterprise wide systems.\u003c/li\u003e\r\n\r\n\u003cli\u003e\u003cstrong\u003eHardware and Systems Technology:\u003c/strong\u003e\r\nComputers and their components, data representation and processing. Computer networks, client/server architecture, operating systems architecture and wireless computing.\u003c/li\u003e\r\n\r\n\u003cli\u003e\u003cstrong\u003eInformation Systems Software Development:\u003c/strong\u003e\r\nSoftware development, systems development, information processing, user interface design and standards, software project management.\u003c/li\u003e\r\n\r\n\u003cli\u003e\u003cstrong\u003eProgramming Concepts and Data Management:\u003c/strong\u003e\r\nProgramming languages and logic, object oriented methods, data types and structures, file types, databases, SQL. Web technologies and development, data warehousing and data mining.\u003c/li\u003e\r\n\r\n\u003cli\u003e\u003cstrong\u003eBusiness, Social, and Ethical Implications and Issues:\u003c/strong\u003e\r\nEconomic effects, business strategies, privacy concerns, security threats and controls, intellectual property and careers in information technology.\u003c/li\u003e\r\n\u003c/ul\u003e34d:T581,\u003cp\u003eThis course is part of \u003ca href=\"https://www.edx.org/professional-certificate/front-end-web-developer-9\"\u003eW3C's \"Front-End Web Developer\" Professional Certificate.\u003c/a\u003e\u003c/p\u003e\n\u003cp\u003eJavaScript"])</script><script>self.__next_f.push([1," lets you add interactive features to your Web sites, including dynamically updated content, controlled multimedia, animated images, and much more. Developed in partnership between W3C and \u003ca href=\"http://univ-cotedazur.fr/en\"\u003eUniversity Côte d'Azur\u003c/a\u003e, this introductory course has been designed to help Web developers have an understanding of the basic concepts of the language. We present JavaScript best practices by means of many interactive examples, some of which being demonstrated in live coding videos.\u003c/p\u003e\n\u003cp\u003eWe use JavaScript in the Web browser. Why JavaScript is worth your time:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eHTML5, CSS and JavaScript are the “classic three” for developers and designers;\u003c/li\u003e\n\u003cli\u003eIt adds interactivity to your Web sites;\u003c/li\u003e\n\u003cli\u003eIt is powerful, easy to learn, and quick to write;\u003c/li\u003e\n\u003cli\u003eIt has great tools (editors, runtimes, lint tools, browsers, and third party libraries) as well as great online support through plenty of active open source communities.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eAt the end of the course, we expect you to be able to read the source code of any JavaScript example found on the Web, learn from it, tweak it, and even – why not? – start contributing to open-source JavaScript projects.\u003c/p\u003e34e:T54a,\u003cp\u003eWhy are hybrid vehicles still more common than battery electric ones? Why are electric vehicles still more expensive than conventional or hybrid ones? In this course, you will get the answers to this and much more. \u003c/p\u003e\n\u003cp\u003eWhile electric motors can improve vehicles regarding performance, energy consumption and emissions, they suffer from high cost and weight of batteries. Smart combinations of electric motors and combustion engines in a hybrid powertrain can combine these strengths with the advantages of combustion engines. \u003c/p\u003e\n\u003cp\u003eThis course is aimed at learners with a bachelor's degree or engineers in the automotive industry who need to develop their knowledge about hybridpowertrains. \u003c/p\u003e\n\u003cp\u003eInthis course, we willexamine different mechanical layouts of hybrid powertrains and how they influence the "])</script><script>self.__next_f.push([1,"performance and complexity of the powertrain. Different sizing of powertrains in micro, mild, full hybrids, as well as plug-in hybrids, is also discussed and you'll learn how they can be modelled and analyzed for example by simulation of driving cycles. You will also learn about the Energy Management system and how this controls the hybrid powertrain modes and when to charge and discharge the battery. \u003c/p\u003e\n\u003cp\u003eAs a result of support from MathWorks, students will be granted access to MATLAB/Simulink for the duration of the course.\u003c/p\u003e34f:T431,\u003cp\u003eIn this course, we will introduce you to the fundamentals of sensor fusion for automotive systems. Key concepts involve Bayesian statistics and how to recursively estimate parameters of interest using a range of different sensors. \u003c/p\u003e\n\u003cp\u003eThe course is designed for students who seek to gain a solid understanding of Bayesian statistics and how to use it to fuse information from different sensors. We emphasize object positioning problems, but the studied techniques are applicable much more generally. The course contains a series of videos, quizzes and hand-on assignments where you get to implement many of the key techniques and build your own sensor fusion toolbox. \u003c/p\u003e\n\u003cp\u003eThe course is self-contained, but we highly recommend that you also take the course ChM015x: Multi-target Tracking for Automotive Systems. Together, these courses give you an excellent foundation to tackle advanced problems related to perceiving the traffic situation around an autonomous vehicle using observations from a variety of different sensors, such as, radar, lidar and camera.\u003c/p\u003e350:T5b5,\u003cp\u003eAutonomous vehicles, such as self-driving cars, rely critically on an accurate perception of their environment. \u003c/p\u003e\n\u003cp\u003eIn this course, we will teach you the fundamentals of multi-object tracking for automotive systems. Key components include the description and understanding of common sensors and motion models, principles underlying filters that can handle varying number of objects, and a selection of the main m"])</script><script>self.__next_f.push([1,"ulti-object tracking (MOT) filters. \u003c/p\u003e\n\u003cp\u003eThe course builds and expands on concepts and ideas introduced in CHM013x: \"Sensor fusion and nonlinear filtering for automotive systems\". In particular, we study how to localize an unknown number of objects, which implies various interesting challenges. We focus on cameras, laser scanners and radar sensors, which are all commonly used in vehicles, and emphasize on situations where we seek to track nearby pedestrians and vehicles. Still, most of the involved methods are more general and can be used for surveillance or to track, e.g., biological cells, sports athletes or space debris. \u003c/p\u003e\n\u003cp\u003eThe course contains a series of videos, quizzes and hands-on assignments where you get to implement several of the most important algorithms. \u003c/p\u003e\n\u003cp\u003eLearn from award-winning and passionate teachers to enhanceyour knowledge at the forefront of research on self-driving vehicles. Chalmers is among the top engineering schools that distinguish itself through its close collaboration with industry.\u003c/p\u003e351:T99b,"])</script><script>self.__next_f.push([1,"\u003cp\u003eEngineers in the automotive industry are required to understand basic safety concepts. With increasing worldwide efforts to develop connected and self-driving vehicles, traffic safety is facing huge new challenges. This course is for students or professionals who have a bachelor's degree in mechanical engineering or similar and who are interested in a future in the vehicle industry or in road design and traffic engineering. It's also of value for people already working in these areas who wantbetter insight into safety issues. \u003c/p\u003e\n\u003cp\u003eThis course teaches the fundamentals of active safety (systems for avoiding crashes or reducing crash consequences) as well as passive safety (systems for avoiding or reducing injuries). Key concepts include in-crash protective systems, collision avoidance, and safe automated driving. The course will introduce scientific and engineering methodologies that are used in the development and assessment of traffic safety and vehicle safety. This includes methods to study the different components of real-world traffic systems with the goal to identify and understand safety problems and hazards. It includes methods to investigate the attitudes and behavior of drivers and other road users as well as recent solutions to improve active safety. Italso includes methods to study human body tolerance to impact and solutions to minimize the injury risk in crashes. \u003c/p\u003e\n\u003cp\u003eStudy topics include crash data analysis and in-situ observational studies of drivers and other road users by the use of instrumented vehicles and roadside camera systems. Solutions in active safety, such as driver alertness monitoring, driver information as well as collision avoidance and collision mitigation systems, will be described. Examples of in-crash protective systems are combinations of traditional restraints such as seat belts and airbags but with advanced functions such as automatic adaption to the individual occupant as well as pre-collision activation based on advanced integrated sensor systems and communication systems. \u003c/p\u003e\n\u003cp\u003eThe course will be based on recorded lectures that use videos and animations to enhance the experience. Online tutorials that access simulation models will give the participants an experience of influencing parameters in active safety and passive safety systems. \u003c/p\u003e\n\u003cp\u003eAs a result of support from MathWorks, students will be granted access to MATLAB/Simulink for the duration of the course.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"352:T488,\u003cp\u003eThis is the third course in the \u003ca href=\"https://www.edx.org/micromasters/ubcx-software-development\"\u003eSoftware Development MicroMasters program\u003c/a\u003e. You will learn how to build larger and more complex software systems using the Java programming language.\u003c/p\u003e\n\u003cp\u003eThe course begins with the topic of data abstraction - from specification to implementation. Particular attention is given to how to write robust tests using JUnit. Then the course expands on these ideas to explore how type hierarchies and polymorphism can be used to decrease redundancy in your code. The course wraps up with a discussion of how to design robust classes.\u003c/p\u003e\n\u003cp\u003eBy the end of the course, you will have a solid foundation in designing software in Java, and be ready to move onto \u003ca href=\"https://edx.org/course/software-construction-object-oriented-ubcx-softconst2x\"\u003eSoftware Construction: Object-Oriented Design\u003c/a\u003e, where you will learn more complex design patterns and principles designing object-oriented programs.\u003c/p\u003e\n\u003cp\u003eLearners who enroll in the Verified track will receive staff grading for the course project and increased interaction with the instructors and staff.\u003c/p\u003e353:T7b6,\u003cp\u003eBroadly speaking, functional programming is a style of programming in which the primary method of computation is the application of functions to arguments. Among other features, functional languages offer a compact notation for writing programs, powerful abstraction methods for structuring programs, and a simple mathematical basis that supports reasoning about programs.\u003c/p\u003e\n\u003cp\u003eFunctional languages represent the leading edge of programming language design, and the primary setting in which new programming concepts are introduced and studied. All contemporary programming languages such as Hack/PHP, C#, Visual Basic, F#, C++, JavaScript, Python, Ruby, Java, Scala, Clojure, Groovy, Racket, … support higher-order programming via the concept of closures or lambda expressions.\u003c/p\u003e\n\u003cp\u003eThis course will use Haskell as the medium for understanding the basic princip"])</script><script>self.__next_f.push([1,"les of functional programming. While the specific language isn't all that important, Haskell is a pure functional language so it is entirely appropriate for learning the essential ingredients of programming using mathematical functions. It is also a relatively small language, and hence it should be easy for you to get up to speed with Haskell.\u003c/p\u003e\n\u003cp\u003eOnce you understand the Why, What and How that underlies pure functional programming and learned to “think like a fundamentalist”, we will apply the concepts of functional programming to “code like a hacker” in mainstream programming languages, using Facebook’s novel Hack language as our main example. This course assumes no prior knowledge of functional programming, but assumes you have at least one year of programming experience in a regular programming language such as Java, .NET, Javascript or PHP.\u003c/p\u003e\n\u003cp\u003eLICENSE\u003cbr /\u003e\n\u003cem\u003eThe course materials of this course are Copyright Delft University of Technology and are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike (CC-BY-NC-SA) 4.0 International License.\u003c/em\u003e\u003c/p\u003e354: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. 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Please enroll only if you are able to finish your coursework in time.\u003c/p\u003e355:T49f,\u003cp\u003eGive your career a boost by mastering how electric, hybrid and conventional combustion engine powertrains are built and how they work. Learn about methods for calculating the performance and energy consumption of powertrains and how to simulate them in different driving cycles. You will also learn about the basic functions of the powertrain components like IC engines, electric machines, transmissions, power electronics and batteries.\u003c/p\u003e\r\n\r\n\u003cp\u003eThe target audience for this program are engineers in the automotive industry who need to develop their knowledge about electric and hybrid powertrains. This course is also aimed at students with a bachelor's degree who want to pursue master level studies in automotive engineering.\u003c/p\u003e\r\n\r\n\u003cp\u003eThis program is derived from both undergraduate and master courses. 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This course is also aimed at students with a bachelor's degree who want to pursue master level studies in automotive engineering.\u003c/p\u003e\r\n\r\n\u003cp\u003eThis program is derived from master level courses. It starts by introducing the basics of Bayesian statistics and recursive estimation theory a"])</script><script>self.__next_f.push([1,"nd then gradually introduces more advanced concepts. The program offers a unique opportunity to gain practical knowledge in sensor fusion and multi-object tracking algorithms (filters).\u003c/p\u003e \r\n\r\n\u003cp\u003eBy the end of this program, you will be able to contribute to the development of sensor fusion and tracking applications for self-driving vehicles. Most of the involved methods, however, are more general and can be used for surveillance or to track, e.g., biological cells, sports athletes or space debris.\u003c/p\u003e357:T563,\u003cp\u003eThis course is the first of a two-course sequence: Introduction to Computer Science and Programming Using Python, and Introduction to Computational Thinking and Data Science. Together, they 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. This run features lecture videos, lecture exercises, and problem sets using Python 3.5. Even if you previously took the course with Python 2.7, you will be able to easily transition to Python 3.5 in future courses, or enroll now to refresh your learning. \u003c/p\u003e\n\u003cp\u003eSince 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\u003e358:T49d,\u003cp\u003eA good algorithm usually comes together with a set of good data structures that allow the algorithm to manipulate the data efficiently. In th"])</script><script>self.__next_f.push([1,"is course, part of the Algorithms and Data Structures MicroMasters program, we consider the common data structures that are used in various computational problems. You will learn how these data structures are implemented in different programming languages and will practice implementing them in our programming assignments. This will help you to understand what is going on inside a particular built-in implementation of a data structure and what to expect from it. You will also learn typical use cases for these data structures.\u003c/p\u003e\n\u003cp\u003eA few examples of questions that we are going to cover in this course are:\u003c/p\u003e\n\u003col\u003e\n\u003cli\u003eWhat is a good strategy of resizing a dynamic array?\u003c/li\u003e\n\u003cli\u003eHow priority queues are implemented in C++, Java, and Python?\u003c/li\u003e\n\u003cli\u003eHow to implement a hash table so that the amortized running time of all operations is O(1) on average?\u003c/li\u003e\n\u003cli\u003eWhat are good strategies to keep a binary tree balanced?\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eWe look forward to seeing you in this course! We know it will make you a better programmer.\u003c/p\u003e359:T522,\u003cp\u003eThis course is one of the 5 courses of an introductory business information systems series, designed to introduce you to the amazing world of Information Technology. \u003c/p\u003e\n\u003cp\u003eThe series of courses is designed so that a professional in a field outside the information technologies (financial, administrative or managerial) acquires the basic knowledge in Information Technology to be able to interact more profitably with the computer and telecommunications specialists of your company or other corporations with which you are related, being able to specify requirements, evaluate workloads and monitor results in a much more effective way. \u003c/p\u003e\n\u003cp\u003eThe syllabus of the series is based on the CLEP Information Systems and Computer Applications exam. \u003c/p\u003e\n\u003cp\u003eIn this course you will learn the basics of software programming. We will address the basic logic behind any computer program, what types and structures of data and files are used, how object-oriented programming works, database management and "])</script><script>self.__next_f.push([1,"SQL language and various concepts and guidelines in web development such as HTML, XML, CSS or javascript, among others. \u003c/p\u003e\n\u003cp\u003eBy completing the series of 5 courses, you will be prepared to interact effectively with specialists in the Information Technology sector (and pass the CLEP ISCA exam if you wish).\u003c/p\u003e35a:T648,\u003cp\u003eThis eight-course Professional Certificate from IBM prepares you with job-ready skills for an entry level data analyst role. Position yourself competitively and power your data analyst career for a job in a thriving market or leverage foundational data skills to explore problems in an increasingly data-driven professional world. 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A willingness to learn, basic computer literacy, comfort working with numbers, high school math, and a desire to enrich your profile with valuable skills is all you need to get started in this course.\u003c/p\u003e\r\n\r\n\u003cp\u003eWith the IBM Data Analyst Professional Certificate you will develop the confidence and portfolio to begin a career as an associate or junior data analyst by learning the essential skills that help professionals in a wide range of job functions and industries explore business problems.\u003c/p\u003e35b:T6cc,\u003cp\u003eThe gen AI market is projected to grow at an impressive 46% CAGR through 2030 (Statista). The demand for te"])</script><script>self.__next_f.push([1,"ch professionals skilled in generative AI engineering is skyrocketing!\r\nThis Generative AI Engineering Professional Certificate gives aspiring generative AI engineers, AI developers, data scientists, machine learning engineers, and AI researchers the critical skills in generative AI, large language models (LLMs), and natural language processing (NLP) that employers are looking for.\u003c/p\u003e\r\n\r\n\u003cp\u003eBy utilizing transformers and LLMs, gen AI engineers create AI systems, applications and agents that generate and process new data—such as images, text, audio, and video.\u003c/p\u003e\r\n\r\n\u003cp\u003eDuring this program, you'll explore AI, generative AI, and prompt engineering, as well as data analysis, machine learning, and deep learning with Python. You'll gain hands-on experience with libraries like SciPy and scikit-learn, and develop applications using frameworks and models like BERT, GPT, and LLaMA. You'll also learn how to build LLM-based NLP applications using tools like Hugging Face Transformers, PyTorch, RAG, and LangChain, while diving deep into tokenization, language models, and transformer methods.\u003c/p\u003e\r\n\r\n\u003cp\u003eThe program offers ample practical experience through hands-on labs and projects you can showcase in interviews. Additionally, you’ll complete a substantial guided project where you’ll build your own real-world generative AI application.\u003c/p\u003e\r\n\r\n\u003cp\u003eIf you're eager to set yourself apart with the highly sought-after generative AI skills that employers are actively looking for, ENROLL TODAY and advance your career in less than 6 months!\r\nPrerequisites: Just basic computer literacy... No prior experience required.\u003c/p\u003e35c: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"])</script><script>self.__next_f.push([1," 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\u003e35d:T474,\u003cp\u003eSpeed is critical in software development. Successful developers are those who are able to quickly learn new technologies and new software systems, and they do this by seeing any software, in any programming language, as common repeating patterns—not just detailed lines of code.\u003c/p\u003e \r\n\r\n\u003cp\u003eIn this MicroMasters program, you will learn this same kind of expert thinking. By working through several software development projects, you will learn specific technologies, including Java, JUnit, IntelliJ IDEA, Typescript and Node.js. Most importantly, you will develop the ability to see the common structures in programs and in tools and learn how to apply these skills to quickly master new technologies.\u003c/p\u003e \r\n\r\n\u003cp\u003eUpon completing this program, you will be able to write programs using a systematic approach and to design programs that are easy to maintain. You will also learn how to use agile methods in order to build software programs that solve real world proble"])</script><script>self.__next_f.push([1,"ms.\u003c/p\u003e \r\n\r\n\u003cp\u003eWith the skills obtained in this program, you will have the confidence to apply for positions that use any programming language or technology.\u003c/p\u003e35e: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.\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\u003e35f: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 environm"])</script><script>self.__next_f.push([1,"ent 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\u003e360: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 course, 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\u003e361:T443,\u003cp\u003eToday, businesses, consumers, and societies leave behind massive amounts of data as a by-product of their activities. Leading-edge companies in every industry are using analytics to replace intuition and guesswork in their decision-making. As a result, managers are collecting and analyzing enormous data sets to discover new patterns and insi"])</script><script>self.__next_f.push([1,"ghts and running controlled experiments to test hypotheses. \u003c/p\u003e\n\u003cp\u003eThis course prepares students to understand business analytics and become leaders in these areas in business organizations. This course teaches the scientific process of transforming data into insights for making better business decisions. It covers the methodologies, issues, and challenges related to analyzing business data. It will illustrate the processes of analytics by allowing students to apply business analytics algorithms and methodologies to business problems. The use of examples places business analytics techniques in context and teaches students how to avoid the common pitfalls, emphasizing the importance of applying proper business analytics techniques.\u003c/p\u003e362: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 project 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 catc"])</script><script>self.__next_f.push([1,"h the eye of an employer. Enroll today and look forward to kickstarting a highly rewarding career.\u003c/p\u003e363:T45f,\u003cp\u003eThis 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 new AP CS Principles curriculum framework.\u003c/p\u003e\r\n\u003cp\u003eAn entry-level course taught by David J. Malan, CS50 AP teaches students how to think algorithmically and solve problems efficiently. Topics include abstraction, algorithms, data structures, encapsulation, resource management, security, software engineering, and web development. Languages include C, PHP, and JavaScript plus SQL, CSS, and HTML. Problem sets inspired by real-world domains of biology, cryptography, finance, forensics, and gaming. As of Fall 2015, the on-campus version of CS50 was Harvard's largest course.\u003c/p\u003e\r\n\u003cp\u003eStudents in high school may receive AP credit for this course provided their school approves the credit and administers the College Board's end-of-year exam. Students who earn a satisfactory score on 9 problem sets (i.e., programming assignments) and a final project are also eligible to receive a verified certificate from HarvardX.\u003c/p\u003e364:T7e7,JavaScript is the most trending programming language on the web today! Facebook, Google, Uber and countless so-called Unicorn startups have now made JavaScript a cornerstone of their technology stack.\u003cbr /\u003e\u003cbr /\u003eThis online course requires no prior knowledge of the JavaScript language. In the first week of the course you will explore the language's basic concepts and fundamentals, and during the second week we will dive into advanced topics such as functions and objects.\u003cbr /\u003e\u003cbr /\u003eWhile JavaScript is recognized primarily for making web pages interactive within web browsers, this course covers the use of the Node.js library - a platform that enables running JavaScript code outside the browser and allows the development of an end-to-end applications in JavaScript. In week three, we will cover the ba"])</script><script>self.__next_f.push([1,"sic architecture of a web application by getting an up-close view of the different parts that make up this application. You will see how data is being exchanged over an Application Programming Interface (API) and what are the different tools and libraries that will allow you to construct such an application. The course will then cover the basic steps required to set up a Node.js server that can process web requests and interact with various set of databases. In the process, you will also be introduced to the Model View Controller (MVC) pattern, a software architecture that organizes the JavaScript application into modules.\u003cbr /\u003e\u003cbr /\u003eFinally, in week four, you will also learn how incredibly easy it is to create beautiful data visualizations that your boss will be proud of. You will gain a basic understanding of the technologies used to present data on the web and will learn how to visualize interactive data using the popular Data Driven Documents (D3) data library.\u003cbr /\u003e\u003cbr /\u003eWhether you are considering a career as a full-stack web developer, pondering developing a mobile app for your next startup or just want to pad your toolbox with a highly sought out skill, this course is definitely for you!365: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 an"])</script><script>self.__next_f.push([1,"d \"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\u003e366: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 toward 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 on"])</script><script>self.__next_f.push([1,"e of the most popular computer science courses ever.\u003c/p\u003e367:T4f7,\u003cp\u003eWith more than 328 million terabytes of data 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\u003e368:T471,\u003cp\u003eThe web is a crucial part of our everyday lives. We rely on websites not just for entertainment and social networking, but for our professions, our finances, our education, and even aspects of our health care. The technologies that run these services are intricate and varied, but there are frameworks and principles that use common languages like HTML and Python that can give you a jump start in building your own web apps.\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 design and implementation of web apps with Python, JavaScript, and SQL using frameworks like Flask, Django, "])</script><script>self.__next_f.push([1,"and Bootstrap.\u003c/p\u003e\r\n\r\n\u003cp\u003eThrough hands-on projects, you'll learn to write and use APIs, create interactive UIs, and leverage cloud services like GitHub and Heroku. You'll emerge with knowledge and experience in principles, languages, and tools that empower you to design and deploy applications. Join now to program your own web applications and gain critical skills in database design, scalability, security, and user experience.\u003c/p\u003e369: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\u003e36a: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,"36b: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\u003e36c:Ta4c,"])</script><script>self.__next_f.push([1,"\u003cp\u003eThis is \u003cstrong\u003eCS50x\u003c/strong\u003e , Harvard University's introduction to the intellectual enterprises of computer science and the art of programming for majors and non-majors alike, with or without prior programming experience. An entry-level course taught by David J. Malan, \u003cstrong\u003eCS50x\u003c/strong\u003e teaches students how to think algorithmically and solve problems efficiently. Topics include abstraction, algorithms, data structures, encapsulation, resource management, security, software engineering, and web development. Languages include C, Python, SQL, and JavaScript plus CSS and HTML. Problem sets inspired by real-world domains of biology, cryptography, finance, forensics, and gaming. The on-campus version of \u003cstrong\u003eCS50x\u003c/strong\u003e , CS50, is Harvard's largest course.\u003c/p\u003e\n\u003cp\u003eStudents who earn a satisfactory score on 9 problem sets (i.e., programming assignments) and a final project are eligible for a certificate. This is a self-paced course–you may take \u003cstrong\u003eCS50x\u003c/strong\u003e on your own schedule.\u003c/p\u003e\n\u003cp\u003eHarvardX requires individuals who enroll in its courses on edX to abide by the terms of the edX honor code. HarvardX will take appropriate corrective action in response to violations of the \u003ca href=\"https://www.edx.org/edx-terms-service\" title=\"Follow link\"\u003eedX honor code\u003c/a\u003e, which may include dismissal from the HarvardX course; revocation of any certificates received for the HarvardX course; or other remedies as circumstances warrant. No refunds will be issued in the case of corrective action for such violations. Enrollees who are taking HarvardX courses as part of another program will also be governed by the academic policies of those programs.\u003c/p\u003e\n\u003cp\u003eHarvardX pursues the science of learning. By registering as an online learner in an HX course, you will also participate in research about learning. Read our \u003ca href=\"https://vpal.harvard.edu/research-statement\" title=\"Follow link\"\u003eresearch statement \u003c/a\u003eto learn more.\u003c/p\u003e\n\u003cp\u003eHarvard University and HarvardX are committed to maintaining a safe and healthy educational and work environment in which no member of the community is excluded from participation in, denied the benefits of, or subjected to discrimination or harassment in our program. All members of the HarvardX community are expected to abide by Harvard policies on nondiscrimination, including sexual harassment, and the edX Terms of Service. If you have any questions or concerns, please contact \u003ca href=\"mailto:harvardx@harvard.edu\"\u003eharvardx@harvard.edu\u003c/a\u003e and/or \u003ca href=\"https://www.edx.org/contact-us\" title=\"Follow link\"\u003ereport your experience through the edX contact form\u003c/a\u003e.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"36d:T671,\u003cp\u003eWith 25 million more project professionals being needed globally by 2030 (Project Management Institute), the demand for talented individuals with good underpinning IT knowledge is exploding. This Information Technology (IT) Fundamentals course is designed specifically for non-technical professionals who want to collaborate effectively with IT teams and make informed decisions. \u003c/p\u003e\n\u003cp\u003eIn this course, you'll learn the essentials of hardware, operating systems, and the foundational concepts of software, programming, and databases. You’ll explore how different types of hardware function, from printers to display devices, and how operating systems manage files and folders. Plus, you’ll discover the basics of software applications, web browsers, programming languages, and how databases store and manipulate data. \u003c/p\u003e\n\u003cp\u003eYou'll also gain an understanding of networking, including network topologies, cables, and how to manage network settings. You’ll learn about storage solutions, from local devices to hosted systems. Plus, you’ll be introduced to cybersecurity fundamentals, covering key concepts like data integrity, threat management, and safe browsing practices. \u003c/p\u003e\n\u003cp\u003eAs you learn, you’ll work on hands-on labs that enable you to apply your new skills in a practical setting. And you’ll test your knowledge with a comprehensive assessment and gain insights into troubleshooting and ticketing systems for IT support. \u003c/p\u003e\n\u003cp\u003eIf you’re a project-oriented professional looking to build a strong, non-technical understanding of IT for your job, ENROLL TODAY and build the job-ready IT skills you need in just 6 weeks.\u003c/p\u003e36e: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,"36f: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\u003e370: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 the 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 so"])</script><script>self.__next_f.push([1,"me 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\u003e371: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\u003e372:T58b,\u003cp\u003eThis programming course takes a unique approach, as it focuses on l"])</script><script>self.__next_f.push([1,"earning 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\u003eDevelop 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\u003e373:T87e,"])</script><script>self.__next_f.push([1,"\u003cp\u003eWhether you’re downloading an app, streaming a video, or clicking a mouse, modern microprocessors are the engines powering your digital life. Arm’s 30-year-plus history of designing energy and power-efficient microprocessors helped fuel the smartphone revolution, and today from the tiniest sensors to the world's most powerful supercomputers, Arm is building the future of computing.\u003c/p\u003e\n\u003cp\u003eThis course will provide you with a deep understanding of the architecture of modern microprocessors. We'll start your learning journey by covering the basics of computer architecture, such as definitions and a description of key components of a microprocessor.\u003c/p\u003e\n\u003cp\u003eWe'll then take a deep dive into important computer architectural concepts and processes. For example, you'll learn how pipelining, branch handling and cache memories can improve the performance of a single-cycle microprocessor. We'll then introduce you to the world of superscalar processors, and how to maximise performance using out-of-order instructions.\u003c/p\u003e\n\u003cp\u003eOur lab exercises will bring to life the theory discussed in the course through a range of simulation tools.\u003c/p\u003e\n\u003cp\u003eAlong the way, we'll provide you with insights from key engineers at Arm, illustrating how and why certain design choices were made so you’ll have the real-world context behind these pivotal architectural decisions.\u003c/p\u003e\n\u003cp\u003eWith over 250 billion Arm-based chips deployed by our vast ecosystem of partners, Arm technology is present wherever computing happens. Be a part of this thriving community and enrol in Computer Architecture Essentials on Arm today.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThis course is aimed at learners who have a basic understanding of computer organisation and programming languages. If you are completely new to the world of microprocessors, we suggest you take our\u003ca href=\"https://www.edx.org/learn/computer-architecture/arm-education-introduction-to-microprocessors?webview=false\u0026campaign=Introduction+to+Microprocessors\u0026source=edx\u0026product_category=course\u0026placement_url=https%3A%2F%2Fwww.edx.org%2Fschool%2Farmeducation\" rel=\"noopener\" target=\"_blank\"\u003e Introduction to Microprocessors\u003c/a\u003e course on edX.\u003c/strong\u003e\u003c/p\u003e"])</script><script>self.__next_f.push([1,"374:T564,\u003cp\u003eThis course is part of \u003ca href=\"https://www.edx.org/es/gfa\"\u003eGlobal Freshman Academy (GFA)\u003c/a\u003e, which means you can earn transferable ASU credit toward your college degree.\u003c/p\u003e\r\n\u003cp\u003eDo you ever say to yourself, \u0026ldquo;there has to be a better way!\u0026rdquo; Then engineering is for you!\u003c/p\u003e\r\n\u003cp\u003eEngineering can be done by everyone, as long as you have a passion for problem solving. In this credit-eligible course, we will walk you through the steps of how to become a true engineer by teaching the engineering design process in a hands-on learning environment.\u003c/p\u003e\r\n\u003cp\u003eThis course is an active introduction to developing an engineering mindset by teaching the necessary skills to be added to your engineering toolbox. You will learn to identify opportunities, imagine new solutions, model your creations, make decisions, build prototypes, and showcase your ideas that impact the world.\u003c/p\u003e\r\n\u003cp\u003eTaught by engineering professors and highlighting industry engineers in action, this course will equip engineers-in-training with skills necessary to compete in today\u0026rsquo;s world of innovation.\u003c/p\u003e\r\n\u003cp\u003eThis is a two-credit course at Arizona State University (FSE 100 Introduction to Engineering). It is strongly encouraged that you consult with your institution of choice to determine how these credits will be applied to their degree requirements prior to transferring the credit.\u003c/p\u003e375:T72d,\u003cp\u003eOrganizations need skilled, forward-thinking Big Data practitioners who can apply their business and technical skills to unstructured data such as tweets, posts, pictures, audio files, videos, sensor data, and satellite imagery, and more, to identify behaviors and preferences of prospects, clients, competitors, and others. ****\u003c/p\u003e\n\u003cp\u003eThis course introduces you to Big Data concepts and practices. You will understand the characteristics, features, benefits, limitations of Big Data and explore some of the Big Data processing tools. You'll explore how Hadoop, Hive, and Spark can help organizations overcome Big Data challenges and reap the rew"])</script><script>self.__next_f.push([1,"ards of its acquisition. \u003c/p\u003e\n\u003cp\u003eHadoop, an open-source framework, enables distributed processing of large data sets across clusters of computers using simple programming models. Each computer, or node, offers local computation and storage, allowing datasets to be processed faster and more efficiently. Hive, a data warehouse software, provides an SQL-like interface to efficiently query and manipulate large data sets in various databases and file systems that integrate with Hadoop.\u003c/p\u003e\n\u003cp\u003eOpen-source Apache Spark is a processing engine built around speed, ease of use, and analytics that provides users with newer ways to store and use big data.\u003c/p\u003e\n\u003cp\u003eYou will discover how to leverage Spark to deliver reliable insights. The course provides an overview of the platform, going into the different components that make up Apache Spark. In this course, you will also learn how Resilient Distributed Datasets, known as RDDs, enable parallel processing across the nodes of a Spark cluster.\u003c/p\u003e\n\u003cp\u003eYou'll gain practical skills when you learn how to analyze data in Spark using PySpark and Spark SQL and how to create a streaming analytics application using Spark Streaming, and more.\u003c/p\u003e376: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 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 realiz"])</script><script>self.__next_f.push([1,"zazione 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\u003e377:T5d6,\u003cp\u003eData structures provide a means to manage large amounts of data for use in databases and internet indexing services. 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 "])</script><script>self.__next_f.push([1,"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/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\u003e378: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\u003e379:T40a,\u003cp\u003eIn this Computer Science co"])</script><script>self.__next_f.push([1,"urse, 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\u003e37a:T6e4,\u003cp\u003eComputing involves processing information. In order to be processed, information must be represented in such a way that it can be manipulated by a machine ubiquitous in today’s society - the computer. \u003c/p\u003e\n\u003cp\u003e**** The computer is a physical device that is based on binary digital logic. From this logic, physical components (hardware) such as memory and processors are designed. These components must fetch, execute and respond to given instructions (software). \u003c/p\u003e\n\u003cp\u003eThis course provides a foundation in the organization and operation of a digital electronic computer starting with the binary digital logic used to represent information and build hardware components. Then, upon this foundation will be built the skills necessary to solve programs through assembly language programs. High-level language algorithms will provide the blueprints for the assembly language solutions.\u003c/p\u003e\n\u003cp\u003eSpecifically, in successfully completing this course you will be able to: \u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eDescribe how computers represent information and"])</script><script>self.__next_f.push([1," apply this knowledge in solving problems with solutions written in assembly language. \u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eDescribe the basic organization of a computer system in terms of binary digital hardware components and apply this knowledge in solving problems with solutions written in assembly language.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eDescribe how instructions are fetched and executed using the digital components and apply this knowledge in solving problems with solutions written in assembly language. \u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eDesign and create assembly language programs that are solutions to problems expressed with algorithms that include high-level language concepts such as variables, data types, repetition, selection, and objects.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e37b:T4a0,\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eFoundations of computer organization\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eInformation representation\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eVon Neumann architecture\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eStorage hierarchy\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eData types and variables in assembly language\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eRepetition in assembly language\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003ePre-test repetition\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003ePost-test repetition\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eSelection in assembly language\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eSingle selection\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eMulti-way selection\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eNesting in assembly language \u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eNesting selection or repetition\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eNesting selection and repetition\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eObjects in assembly language\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eProperties\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eMethods\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eData structures in assembly language\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eArrays\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eLists\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eFiles in assembly language\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eSequential access\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eRandom access\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eIBM tools\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eVSAM Demystified\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eDB2 Overview\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eCICS Overview\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/li\u003e\n\u003c/ul\u003e37c: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,"37d: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 computer science presented in C++ to ease learning of other programming languages; and develop a sense of comfort and confidence while programming.\u003c/p\u003e37e: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 "])</script><script>self.__next_f.push([1,"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\u003e37f: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\u003e380: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 cod"])</script><script>self.__next_f.push([1,"ing. 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\u003e381: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 you 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 k"])</script><script>self.__next_f.push([1,"ey component of this course.\u003c/p\u003e382: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,"383:Tcf2,"])</script><script>self.__next_f.push([1,"\u003cp\u003e将棋を題材にプログラミングの基礎と様々な工夫を学びます。\u003c/p\u003e\n\u003cp\u003eプログラムの実行環境として、MATLAB版の将棋プログラム「MT将棋（※）」を使用します。MATLABは数値計算を扱うことが得意なプログラミング言語で，MATLAB版の「MT将棋」は、その特徴を生かしながらコーディングされています。\u003c/p\u003e\n\u003cp\u003e本コースでは「MT将棋」のすべてのコードを詳細に説明することはしませんが、コードの要点をピックアップした解説を通してプログラミングの基本や考え方の一端を学ぶことができます。\u003c/p\u003e\n\u003cp\u003eMATLABの実行環境をお持ちの受講者の方は、実際に「MT将棋」を実行したり、修正したりしながら学ぶことができます。MATLABの実行環境をお持ちでない受講者の方には、MATLAB開発元のMathWorks社の協力により、本コースの受講者限定で、WebブラウザーからMATLABを使用できるMATLAB Onlineの期間限定（約9週間）ライセンスが発行されます。\u003c/p\u003e\n\u003cp\u003e（※）MT将棋：約50の関数ファイルからなる、合計で約2100行、約9500単語、ファイルサイズ約86KBのMATLABコードです。2018年に実施された「小学生向け将棋プログラミング講習会」（主催：東京工業大学工学院、共同主催：電子情報通信学会東京支部、後援：日本将棋連盟、協力：大田区立清水窪小学校・東工大将棋部）に向けて開発が開始され、その後、更新されてきました。\u003c/p\u003e\n\u003cp\u003e本コースは\u003ca href=\"https://www.wise-sss.titech.ac.jp\" title=\"東京工業大学超スマート社会卓越教育院\"\u003e東京工業大学超スマート社会卓越教育院\u003c/a\u003eが制作し、提供しています。\u003c/p\u003e\n\u003cp\u003e----------\u003c/p\u003e\n\u003cp\u003eIn this course, you will learn the basics of programming and various techniques of coding with computer Shogi. The course uses \"MT Shogi(*)\", a Shogi program that runs on MATLAB. MATLAB is a programming language that excels at handling numerical calculations, and \"MT Shogi\" was implemented to take advantage of such high computational power of MATLAB.\u003c/p\u003e\n\u003cp\u003eIn this course, we will not explain all the code of \"MT Shogi\" in detail, but you will learn fundamental concepts of programming through easy-to-understand explanations on the key points of \"MT Shogi\".\u003c/p\u003e\n\u003cp\u003eParticipants who have a MATLAB environment can learn by actually running and revising \"MT Shogi\". For participants who do not have a MATLAB environment, MathWorks, the developer of MATLAB, will provide a limited time (approximately 9 weeks) license for MATLAB Online, which allows participants to use MATLAB from a web browser, exclusively for this course.\u003c/p\u003e\n\u003cp\u003e(*) MT Shogi: MATLAB code consisting of about 50 function files with a total of about 2100 lines, about 9500 words, and a file size of about 86KB. This program was first developed for a \"Shogi programming workshop for elementary school students\" in 2018, and has been updated since then.\u003c/p\u003e\n\u003cp\u003eThis course is produced and offered by \u003ca href=\"https://www.wise-sss.titech.ac.jp/en/\" title=\"Tokyo Tech Academy for Super Smart Society (WISE-SSS)\"\u003eTokyo Tech Academy for Super Smart Society (WISE-SSS)\u003c/a\u003e.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"384:T4eb,\u003cp\u003eAn introduction to programming using a language called Python. Learn how to read and write code as well as how to test and \"debug\" it. Designed for students with or without prior programming experience who'd like to learn Python specifically. Learn about functions, arguments, and return values (oh my!); variables and types; conditionals and Boolean expressions; and loops. Learn how to handle exceptions, find and fix bugs, and write unit tests; use third-party libraries; validate and extract data with regular expressions; model real-world entities with classes, objects, methods, and properties; and read and write files. Hands-on opportunities for lots of practice. 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. \u003c/p\u003e\n\u003cp\u003eWhereas \u003ca href=\"https://www.edx.org/course/introduction-computer-science-harvardx-cs50x\"\u003eCS50x\u003c/a\u003e itself focuses on computer science more generally as well as programming with C, Python, SQL, and JavaScript, this course, aka CS50P, is entirely focused on programming with Python. You can take CS50P before CS50x, during CS50x, or after CS50x. But for an introduction to computer science itself, you should still take CS50x!\u003c/p\u003e385:Tb6e,"])</script><script>self.__next_f.push([1,"\u003cp\u003eA quantum computer is a new class of computer that promises to find solutions to specific problems, which a classical computer either cannot solve or will take much longer to solve. Unlike classical computers, a quantum computer is built-up with qubits and utilizes concepts such as the superposition principle and quantum entanglement to solve complex problems.\u003c/p\u003e\n\u003cp\u003eThis course aims to provide you with an introduction to this exciting field beyond the theoretical. It will focus on understanding the hardware of a quantum computer, provide basic applications, and introduce the software and programming language to run a quantum computer.\u003c/p\u003e\n\u003cp\u003eWhat makes this course stand out is the utilization of QuTech’s Quantum Inspire (QI) to demonstrate the capabilities of quantum computers. Using the real quantum hardware and the various simulation tools provided by the platform, you will be able to experiment and execute quantum algorithms on a real quantum computer, enabling you to discover the possibilities that this new technology offers.\u003c/p\u003e\n\u003cp\u003eThe course starts with a brief overview of the quantum hardware, that makes a quantum computer, and of quantum algorithms that can be run on a quantum computer. After this, you will delve into the various tools offered by QI, including cQASM, a programming language developed to operate on a quantum computer, and QI Software Development Kit (SDK), that allows you to develop and execute your own algorithms on the quantum computers developed by QuTech.\u003c/p\u003e\n\u003cp\u003eIf you have made it this far, you will have mastered the essential tools for developing and investigating quantum computing applications and will have the opportunity to join a growing community of developers! Upon successful completion of the course, participants from the EU (both audit and verified) are entitled to a QTIndu certificate.\u003c/p\u003e\n\u003cp\u003eThis course was developed by a team of experts in quantum computing infrastructure and quantum information from TU Delft, drawing on the extensive expertise of leading experts in quantum technology from QuTech.\u003c/p\u003e\n\u003cp\u003eThis project has received funding from the European Union's Digital Europe Programme under grant agreement no. 101100757.\u003c/p\u003e\n\u003cp\u003eThis course has been developed with the support of the European-funded project QTIndu (Quantum Technologies courses for Industry). The aim of QTIndu is to provide solutions specifically tailored to the needs of industry. Together with ten other partners, which include universities, research institutes and private companies, we are creating training courses in quantum technologies for professionals in various industries. Learn more on qtindu.eu (https://qtindu.eu/).\u003c/p\u003e\n\u003cp\u003e\u003cimg src='https://courses.edx.org/asset-v1:DelftX+QCQN1x+3T2024+type@asset+block@Logo_QTIndu_and_EU_funded.PNG' width='100%' height='' alt='Logo of the European-funded project QTIndu (Quantum Technologies courses for Industry)' /\u003e\u003c/p\u003e"])</script><script>self.__next_f.push([1,"386:T774,\u003cp\u003eIl corso ha come obiettivo la presentazione delle basi logico/matematiche della elaborazione automatica dell’Informazione e la presentazione delle tecnologie dell’Informatica e delle Telecomunicazioni. La teoria dell’informazione, elaborata da Shannon, è esaminata in tutti i suoi aspetti. Si approfondiranno i concetti di base relativi al Sistema Operativo con riferimento a Windows e alle Graphical User Interfaces. Sono illustrate poi attività di programmazione procedurale e la programmazione Object Oriented in relazione al Coding. Si introducono poi, le reti di calcolatori e gli impianti di trasmissione con attenzione per le reti telematiche nelle forme di Reti Locali, Geografiche e rete Internet. Il World Wide Web è descritto con l’introduzione del protocollo HTTP e della sua applicazione con i servizi web: HTML e CSS. Si descrivono poi in dettaglio Content Management Systems come Wiki e Wordpress. Il corso si conclude con le Reti Sociali e una panoramica sul futuro di internet.\u003c/p\u003e\n\u003cp\u003eThe aim of this course is to present the mathematical/logic basis underpinning automatic elaboration of Information and to introduce computing and telecommunications technologies. Shannon’s Information theory is first introduced as well as the basic concepts behind computer systems organisation, operating systems and Graphical User Interfaces. Learners then explore procedural programming and Object Oriented programming as major approaches to coding. Computer networks and transmission systems are then presented, focusing on telematic networks at the local, geographic and Internet level. The World Wide Web is described with the introduction of the HTTP protocol and its application in web services: HTML and CSS. Content Management Systems like Wiki and Wordpress are described in detail and the course concludes with Social Networks and an overview of the future of the Internet.\u003c/p\u003e387:T4c8,\u003cp\u003eAn introduction to programming using Scratch, a visual programming language via which aspiring programmers can write co"])</script><script>self.__next_f.push([1,"de 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\u003e388:T5aa,\u003cp\u003eIn this course, you will learn the principles of C programming and start coding hands-on in a browser tool that will provide instant feedback on your code. \u003c/p\u003e\r\n\u003cp\u003eThe C programming language is one of the most stable and popular programming languages in the world. It helps to power your smartphone, your car's navigation system, robots, drones, trains, and almost all electronic devices. C is used in any circumstances where speed and flexibility are important, such as in embedded systems or high-performance computing. \u003c/p\u003e\r\n\u003cp\u003eIn this course, you will get started with C and learn how to write your first programs, how to make simple computations and print the results to the screen, how to store values in variables and how to repeat instructions using loops. \u003c/p\u003e\r\n\u003cp\u003eBeginners, even those without any programming experience, will be able to immediately start coding in C with the help of powerful yet simple coding tools right"])</script><script>self.__next_f.push([1," within the web browser. No need to install anything! \u003c/p\u003e\r\n\u003cp\u003eWe are excited to introduce you to the world of coding and launch you along your path to becoming a skilled C programmer! \u003c/p\u003e\r\n\u003cp\u003eThis is the first course in the C Programming with Linux Professional Certificate program. This series of seven short courses will establish your programming skills and unlock doors to careers in computer engineering. \u003c/p\u003e\r\n\u003cp\u003eThis course has received financial support from the Patrick \u0026amp; Lina Drahi Foundation.\u003c/p\u003e389:T4a5,\u003cp\u003eInthis course, part of the C Programming with Linux Professional Certificate program,you will learn to use logical statements and arrays in C. Logical statements are used for decision-making with follow-up instructions, based on conditions you define. Arrays are used to store, keep track of, and organize larger amounts of data. You will furthermore implement some fundamental algorithms to search and sort data.\u003c/p\u003e\r\n\u003cp\u003eWithin moments of this course, you will be coding hands-on in a new browser tool developed specifically for this course, receiving instant feedback on your code. No need to install anything!\u003c/p\u003e\r\n\u003cp\u003eWhy learn C? Not only is it one of the most stable and popular programming languages in the world, it's also used to power almost all electronic devices. The C programming language represents one of the building blocks of modern computer information technology.\u003c/p\u003e\r\n\u003cp\u003eBy the end of this course, you will have gained experience with programming concepts that are foundational to any programming language and be one step closer to a career in computer engineering.\u003c/p\u003e\r\n\u003cp\u003eThis course has received financial support from the Patrick \u0026amp; Lina Drahi Foundation.\u003c/p\u003e38a:T492,\u003cp\u003eMaintaining and updating software is an important activity for a Technical Support role. There are many types of software, and understanding software can be overpowering. This course introduces the fundamentals of software and how to manage software from an information technology (IT) perspective. You'll be introduced to va"])</script><script>self.__next_f.push([1,"rious types of software, ranging from the operating system running on your mobile phone to the applications that run databases on your computer at work. You'll also learn about cloud computing, web browsers, software development, programming languages, and database fundamentals.\u003c/p\u003e\n\u003cp\u003eAfter completing this course, you will better understand software processes and gain confidence in using and securing software applications. You will also review installing and managing web browsers, extensions, and plug-ins and keeping web browsers secure and updated.\u003c/p\u003e\n\u003cp\u003eAdditionally, you'll discover how cloud-based technologies help businesses create and deploy applications faster. This course provides several real-world inspired hands-on labs and activities to demonstrate your skills in programming with Python and working with a database.\u003c/p\u003e38b:T5bc,\u003cp\u003eToday, computer graphics is a central part of our lives, in movies, games, computer-aided design, virtual reality, virtual simulators, visualization and even imaging products and cameras. This course, part of the Virtual Reality (VR) Professional Certificate program, teaches the basics of computer graphics that apply to all of these domains.\u003c/p\u003e\n\u003cp\u003eStudents will learn to create computer-generated images of 3D scenes, including flybys of objects, make a real-time scene viewer, and create very realistic images with raytracing. We will start with a simple example of viewing a teapot from anywhere in space, understanding the basic mathematics of virtual camera placement. Next, you will learn how to use real-time graphics programming languages like OpenGL and GLSL to create your own scene viewer, enabling you to fly around and manipulate 3D scenes. Finally, we will teach you to create highly realistic images with reflections and shadows using raytracing.\u003c/p\u003e\n\u003cp\u003eThis course runs for 6 weeks and consists of four segments. Each segment includes an individual programming assignment:\u003c/p\u003e\n\u003col\u003e\n\u003cli\u003eOverview and Basic Math (Homework 0: 10% of grade)\u003c/li\u003e\n\u003cli\u003eTransformations (Homework 1: 2"])</script><script>self.__next_f.push([1,"0% of grade)\u003c/li\u003e\n\u003cli\u003eOpenGL and Lighting (Homework 2: 35% of grade)\u003c/li\u003e\n\u003cli\u003eRaytracing (Homework 3: 35% of grade)\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThis term, students who earn a total score of 50% or greater will have passed the course and may obtain a certificate from UC San DiegoX.\u003c/p\u003e38c:T434,\u003cp\u003eCode and run your first Python program in minutes without installing anything! ****\u003c/p\u003e\n\u003cp\u003eThis course is designed for learners with limited coding experience, providing a solid foundation of not just Python, but core Computer Science and software development topics that can be transferred to other languages. The modules in this course cover object-oriented programming, inheritance, encapsulation, polymorphism, and other object-related topics. Completion of the prior 2 courses in this program is recommended.\u003c/p\u003e\n\u003cp\u003eTo allow for a truly hands-on, self-paced learning experience, this course is video-free. Assignments contain short explanations with images and runnable code examples with suggested edits to explore code examples further, building a deeper understanding by doing. You’ll benefit from instant feedback from a variety of assessment items along the way, gently progressing from quick understanding checks (multiple choice, fill in the blank, and un-scrambling code blocks) to small, approachable coding exercises that take minutes instead of hours.\u003c/p\u003e38d: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 p"])</script><script>self.__next_f.push([1,"rocessor 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\u003e38e:T402,\u003cp\u003eCode and run your first Python program in minutes without installing anything! ****\u003c/p\u003e\n\u003cp\u003eThis course is designed for learners with limited coding experience, providing a solid foundation of not just Python, but core Computer Science and software development topics that can be transferred to other languages. The modules in this course cover strings, functions, files, and recursion. Completion of Python: Basics Skills before taking this course is recommended.\u003c/p\u003e\n\u003cp\u003eTo allow for a truly hands-on, self-paced learning experience, this course is video-free. Assignments contain short explanations with images and runnable code examples with suggested edits to explore code examples further, building a deeper understanding by doing. You’ll benefit from instant feedback from a variety of assessment items along the way, gently progressing from quick understanding checks (multiple choice, fill in the blank, and un-scrambling code blocks) to small, approachable coding exercises that take minutes instead of hours.\u003c/p\u003e38f:T46d,\u003cp\u003eIn this course, we will examine a key concept, foundational to any programming language: the usage of memory.\u003c/p\u003e\r\n\u003cp\u003eThis course builds upon the basic concept of pointers, discussed in C Programming: Modular Programming and Memory Management, and introduces the more advanced usage of pointers and pointer arithmetic. Arrays of pointers and multidimensional arrays are addressed, and you will learn how to allocate memory for your own data during program execution. This is called dynamic memory allocation at runtime using pointers.\u003c/p\u003e\r\n\u003cp\u003eWithin moments you will be"])</script><script>self.__next_f.push([1," coding hands-on in a new browser tool developed for this course, receiving instant feedback on your code. No need to install anything!\u003c/p\u003e\r\n\u003cp\u003eIn this course, you will gain experience with programming concepts that are foundational to any programming language.\u003c/p\u003e\r\n\u003cp\u003eAt the end of this short course, you will reach the fourth milestone in the C Programming with Linux Professional Certificate program, unlocking the door to a career in computer engineering.\u003c/p\u003e\r\n\u003cp\u003eThis course has received financial support from the Patrick \u0026amp; Lina Drahi Foundation.\u003c/p\u003e390: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 complete 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\u003e391:T4b3,\u003cp\u003eIn this course, part of the C Programming with Linux Professional Certificate program, you will define your own data types in C, and use the newly created types to more efficiently store and process "])</script><script>self.__next_f.push([1,"your data. \u003c/p\u003e\r\n\u003cp\u003eMany programming languages provide a number of built-in data types to store things such as integers, decimals, and characters in variables, but what if you wanted to store more complex data? \u003c/p\u003e\r\n\u003cp\u003eDefining your own data types in C allows you to more efficiently store and process data such as a customer's name, age and other relevant data, all in one single variable! \u003c/p\u003e\r\n\u003cp\u003eThis course will provide a hands-on coding experience in a new browser tool developed for this course that will allow you to receive instant feedback on your code. No need to install anything! You will also gain experience with programming concepts that are foundational to any programming language. \u003c/p\u003e\r\n\u003cp\u003eAt the end of this short course, you will reach the fifth milestone of the C Programming with Linux Professional Certificate program, unlocking the door to a career in computer engineering. \u003c/p\u003e\r\n\u003cp\u003eThis course has received financial support from the Patrick \u0026amp; Lina Drahi Foundation.\u003c/p\u003e392:T5ff,\u003cp\u003eIn this course, part of the C Programming with Linux Professional Certificate program, you will be introduced to the concept of modular programming: that is, dividing up more complex tasks into manageable pieces. \u003c/p\u003e\r\n\u003cp\u003eWithin moments you will be coding hands-on in a new browser tool developed for this course, receiving instant feedback on your code. No need to install anything! \u003c/p\u003e\r\n\u003cp\u003eYou will learn how to write your own functions (just like functions in mathematics for example). You will also gain insight into a computer's architecture and learn how its memory is organized. \u003c/p\u003e\r\n\u003cp\u003eGiven the vast amount of memory computers have these days, how does your program remember where a certain variable is stored? This brings about the important topic of how memory is efficiently addressed inside a computer, and with it, the topic of pointers. \u003c/p\u003e\r\n\u003cp\u003ePointers are often considered the most difficult part and main struggle for C program developers. We will introduce you to this central topic with our novel and innovative "])</script><script>self.__next_f.push([1,"visualization tools and show you precisely how pointers work. No need to struggle! \u003c/p\u003e\r\n\u003cp\u003eThe programming concepts you will gain in this course are foundational to any programming language. \u003c/p\u003e\r\n\u003cp\u003eBy the end of this short course, you willhave reached the third milestonein the C Programming with Linux Professional Certificate program, unlocking the door to a career in computer engineering. \u003c/p\u003e\r\n\u003cp\u003eThis course has received financial support from the Patrick \u0026amp; Lina Drahi Foundation.\u003c/p\u003e393: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 programs 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 "])</script><script>self.__next_f.push([1,"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\u003e394: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\u003e395: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, present, 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"])</script><script>self.__next_f.push([1,". \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\u003e396: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 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 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"])</script><script>self.__next_f.push([1,"\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\u003e397: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 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.\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\u003e398:T790,Arduino uno is a small"])</script><script>self.__next_f.push([1," computer used to connect the physical world to the digital world. Introduced in the early 2000s as a tool for design students who had no experience in electronics programming, it has become the most popular electronics prototyping tool, especially for IoT product development, a sector which companies are estimated to spend\u0026nbsp;more than $300 billion a year on by 2020.\u003cbr /\u003e\u003cbr /\u003eWith several million users and counting, Arduino gives anyone the power to innovate -\u0026nbsp; from designing a connected object for their own home to launching a prototype of a product\u0026nbsp;for their own business.\u003cbr /\u003e\u003cbr /\u003eThis course is ideal for students in design or electronics. It's also highly applicable for engineers, designers, or developers who want to strengthen their skills in interactive electronics. It suits those who are either completely new to Arduino or want to practice their skills with concrete coding challenges.\u003cbr /\u003e\u003cbr /\u003eYou will learn about electronics and programming, starting from the very basics and building up to mastery of the Arduino platform. You will learn how to use sensors to detect external events, such as light or sound, and how to perform an action linked to these events.\u003cbr /\u003e\u003cbr /\u003eThe course also provides a natural introduction to the world of FabLabs, an international network of over a thousand spaces where people can access digital manufacturing machines and practice using Arduino alongside other makers.\u003cbr /\u003e\u003cbr /\u003eThe course also provides recommendations of where learners can easily purchase an arduino starter kit to get the right hardware to set themselves up or online simulators which work well as alternatives if they aren't quite ready to invest in the material yet.\u003cbr /\u003e\u003cbr /\u003eWant to get creative? You\u0026rsquo;ll see that everyone can become a maker! Join us!\u003cbr /\u003e\u003cbr /\u003eThis course\u0026nbsp;has received financial support from\u0026nbsp;the Patrick and Lina Drahi Foundation.399:T478,\u003cp\u003eLearn Python by doing! Codio courses are designed to engage and excite beginners. Instead of reading or watching a video, "])</script><script>self.__next_f.push([1,"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 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\u003e39a: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,"39b:Tba0,"])</script><script>self.__next_f.push([1,"\u003cp\u003ePrepare yourself for the quantum future! This program features step-by-step instructions on how to program and run simulations utilizing two of QuTech’s demonstrators: Quantum Network Explorer (QNE) and Quantum Inspire (QI). After a brief overview of the basic theoretical underpinnings of quantum internet and quantum hardware, QuTech’s experts will guide you through diverse examples on how to run your own simulations on the demonstrators.\u003c/p\u003e\r\n\r\n\u003cp\u003eIn the first course, Quantum Communication and Quantum Network Explorer, you will use The Quantum Network Explorer (QNE) to demonstrate the capabilities of quantum networks. The course starts with a brief overview of quantum networks. After this, you will delve into the various tools offered by QNE, including the QNE Community Application Library (QNE-CAL), the QNE Application Development Kit (QNE-ADK), and SquidASM, an advanced application simulator developed by QuTech. Further, you will learn how to modify existing applications and create new ones from scratch using QNE’s Application Development Kit (QNE-ADK). You will also receive a comprehensive tutorial on SquidASM, a software package designed for advanced simulations of quantum network applications.\u003c/p\u003e \r\n\r\n\u003cp\u003eIn the second course, Quantum Hardware and its Applications with Quantum Inspire, you will use Quantum Inspire (QI) to demonstrate the capabilities of quantum computers. The course starts with a brief overview of the quantum hardware that makes a quantum computer, and quantum algorithms that can be run on a quantum computer. After this, you will delve into the various tools offered by QI, including cQASM, a programming language developed to operate on a quantum computer, and QI Software Development Kit (SDK), that allows you to develop and execute your own algorithms on the quantum computers developed by QuTech.\u003c/p\u003e\r\n\r\n\u003cp\u003eAfter completion of the program, you will have mastered essential tools for developing and investigating quantum computing applications and will have the opportunity to join a growing community of developers! Upon successful completion of either course, participants from the EU (both audit and verified) are entitled to a QTIndu certificate.\u003c/p\u003e\r\n\r\n\u003cp\u003eThis project has received funding from the European Union's Digital Europe Programme under grant agreement no. 101100757.\u003c/p\u003e\r\n\r\n\u003cp\u003eThese courses have been developed with the support of the European-funded project QTIndu (Quantum Technologies courses for Industry). The aim of QTIndu is to provide solutions specifically tailored to the needs of industry. Together with ten other partners, which include universities, research institutes and private companies, we are creating training courses in quantum technologies for professionals in various industries. Learn more on \u003ca href=\"https://qtindu.eu/\"\u003eqtindu.eu\u003c/a\u003e.\u003c/p\u003e\r\n\r\n\u003cp\u003e\u003cimg src=\"https://images.ctfassets.net/ii9ehdcj88bc/4D4rg22M0eQYervWW2OL55/ca695a4d2c590ddd05a1dc349e9480cc/eu-qtindu.png\"\u003e\u003c/p\u003e"])</script><script>self.__next_f.push([1,"39c: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, contraction 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\u003e39d: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 p"])</script><script>self.__next_f.push([1,"erform 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\u003e39e: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 roster 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 exercise"])</script><script>self.__next_f.push([1,"s 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\u003e39f: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\u003e3a0: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, s"])</script><script>self.__next_f.push([1,"uch 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\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\u003e3a1: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. There are also comprehensive quizzes at the end of each seg"])</script><script>self.__next_f.push([1,"ment to measure your understanding of the content.\u003ca href=\"http://www.ivado.ca/en\"\u003e\u003c/a\u003e\u003c/p\u003e\n\u003cp\u003eIVADO is a scientific and economic data science hub bridging industrial, academic and governmental partners with expertise in digital intelligence. One of its missions is to contribute to the advancement of digital knowledge and train new generations of bias-aware data scientists.\u003c/p\u003e\n\u003cp\u003eWelcome to this enlightening journey in the world of ethical AI!\u003c/p\u003e3a2:T4cf,\u003cp\u003eSame as the prerequisite course, we do not just enumerate side-channel effects and how to exploit them. We provide you with the experience of learning about side channels, in a group of students, living in a shared appartment. Together with them you will figure out that what software side channels are, why they are relevant for cybersecurity, in particular in our modern digital lifes, where all our secrets are stored on computers that can be subverted using side channels.\u003c/p\u003e\n\u003cp\u003eIn this course, we get one step closer to hugely impactful attacks like Meltdown and Spectre, which internally use side channels. We will learn about different simple software-based side channels and how they can be exploited. We will cover the basics, requiring some programming skills. We again focus on the security or side-channel mindset, as a crucial take-away for you, that you will be able to apply on a day-to-day basis in your studies, your job, and your personal life. You will extend your view on side channels and be able to assess risks in technical contexts in detail. In a set of small exercises, you will demonstrate that you understood the basics, and are able to find and exploit side channels in small software programs.\u003c/p\u003e3a3:T66c,\u003cp\u003eIl linguaggio di programmazione è uno degli strumenti che abbiamo per interpretare e risolvere i problemi di tutti i giorni. Un linguaggio che è alla base di problemi comuni, come le previsioni del tempo o l'analisi della deformazione di una struttura di un'auto in un incidente stradale. \u003c/p\u003e\n\u003cp\u003eQuesto corso fornisce un’introduzione alle "])</script><script>self.__next_f.push([1,"metodologie e agli strumenti per la risoluzione di problemi attraverso l'uso del computer. Sarai guidato nell'individuazione di metodologie di progetto, sviluppo ed analisi degli algoritmi di base per il calcolo scientifico nonché all’uso dei principali strumenti di calcolo (hardware e software), con particolare riguardo all’influenza che questi ultimi esercitano sullo sviluppo degli algoritmi stessi. \u003c/p\u003e\n\u003cp\u003eUna volta completato questo corso, segui la seconda parte con \u003ca href=\"https://www.edx.org/course/laboratorio-di-programmazione-strumenti-e-programmi\"\u003eLaboratorio di programmazione: strumenti e programmi\u003c/a\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProgramming Lab\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eProgramming languages offera solution for interpreting and solving everyday problems. A language that underlies basic problems, like forecasting the weather, or understanding the dynamics of a car accident from the damage to the car. \u003c/p\u003e\n\u003cp\u003eThis course introduces students to the various methods and tools for problem-solving via computer. You will learn how to select the best methodology for your project, how to develop and analyze basic algorithms for scientific calculation, and how to use the main calculation tools (hardware e software). You will also see how these tools influence the development of algorithms.\u003c/p\u003e3a4: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,"3a5: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,"3a6:T477,\u003cp\u003eAlgorithmics and programming are fundamental skills for engineering students, data scientists and analysts, computer hobbyists or developers.\u003c/p\u003e\n\u003cp\u003eLearning how to program algorithms can be tedious if you aren’t given an opportunity to immediately practice what you learn. In this course, you won't just focus on theory or study a simple catalog of methods, procedures, and concepts. Instead, you’ll be given a challenge wherein you'll be asked to beat an algorithm we’ve written for you by coming up with your own clever solution.\u003c/p\u003e\n\u003cp\u003eTo be specific, you’ll have to work out a route faster than your opponent through a maze while picking up objects.\u003c/p\u003e\n\u003cp\u003eEach week, you will learn new material to improve your artificial intelligence in order to beat your opponent. This structure means that as a learner, you’ll confront each abstract notion with a real-world problem.\u003c/p\u003e\n\u003cp\u003eWe’ll go over data-structures, basic and advanced algorithms for graph theory, complexity/accuracy trade-offs, and even combinatorial game theory.\u003c/p\u003e\n\u003cp\u003eThis course has received financial support from the Patrick and Lina Drahi Foundation.\u003c/p\u003e3a7: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 "])</script><script>self.__next_f.push([1,"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\u003e3a8: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"])</script><script>self.__next_f.push([1,"/p\u003e3a9: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 built 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\u003e3aa"])</script><script>self.__next_f.push([1,":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 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\u003e3ab:T46b,\u003cp\u003eMalicious software, or malware, is typically delivered over a network and is designed to cause disruption to a computer, client, server, or network. Disruptions can include leaked private information, unauthorized access to information or systems, blocked user access, interference with security and privacy, or numerous other variations of attacking systems. \u003c/p\u003e\n\u003cp\u003eMalware analysis dissects malware to gather information about the malware functionality, how the system was compromised so that you can defend against future attacks. \u003c/p\u003e\n\u003cp\u003eAssembly is a low-level language that is used to communicate with the machine. Assembly programming is writing human-readable machine codes or machine instructions that are directly read by the computer. All high-level languages compiled programs like C or C++ can be broken down, analyzed, and understood using Assembly language with t"])</script><script>self.__next_f.push([1,"he help of a debugger. This process is known as reverse engineering. Understanding what an executable program does is easy if you have direct access to the source code. But if not, such as the case with malware, learning Assembly can be helpful.\u003c/p\u003e3ac: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,"3ad:T74f,\u003cp\u003eThe Mechatronics Revolution is upon us. Never before has it been easier to build robotic devices and computer-controlled machines. The confluence of low-cost embedded computers, sensors, and actuators has made experimentation and prototyping easier than ever. Course modules will explore the mechatronics design process, fundamentals of microcontrollers, embedded systems programming, actuator control, and sensor interfacing. Through several hands-on labs, students will solidify their knowledge of core mechatronics concepts and gain real-world experience building their own mechatronic systems. Upon successful completion of the course, students will be equipped with the fundamental knowledge they need to harness the Mechatronics Revolution. \u003c/p\u003e\n\u003cp\u003eTo complete the lab assignments in the course, students must purchase the mechatronics lab kit, \u003ca href=\"https://www.mouser.com/new/texas-instruments/ti-mechatronics-revolution/\"\u003eTI-RSLK-Mechkit\u003c/a\u003e (available on Mouser.com for $119). Purchase of the kit or its components is required for all students on the Verified track. The kit provides all the materials needed to complete the lab assignments and build a small robot. Currently Mouser does not deliver to a few specific regions and countries such as Nigeria. Students who cannot purchase the kit from Mouser can purchase the parts included in the kit separately from other vendors as described \u003ca href=\"https://courses.edx.org/asset-v1:GTx+mechatronics+3T2019+type@asset+block@Note-on-TI-RSLK-Mechkit.pdf\"\u003ehere\u003c/a\u003e. \u003c/p\u003e\n\u003cp\u003eAudit students who do not wish to complete the labs but want to follow the lectures may optionally purchase the \u003ca href=\"https://www.ti.com/tool/MSP-EXP432P401R#buy\"\u003eTI MSP432 Launchpad\u003c/a\u003e development board for $19.99. This will allow students to practice microcontroller programming skills as demonstrated in the course videos.\u003c/p\u003e3ae:T663,\u003cp\u003eIn today’s world, businesses can only survive and remain competitive if they embrace and leverage core technologies like cloud, AI, and data science. Thes"])</script><script>self.__next_f.push([1,"e 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\u003e3af:T687,\u003cp\u003eNow is a great time to launch a rewarding career in Information Technology (IT) support - no experience or degree is required to get started. The US Bureau of Labor Statistics forecasts a 9% growth in jobs through 2030, averaging 70,000 openings each year, and a medium salary of $58,000 annually for an entry-level Computer Support Specialist. With over 400,000 US job openings, Computer Tech Support Specialists are in high demand.\u003c/p\u003e \r\n \r\n\u003cp\u003eIn this self-paced, certificate program for beginners, you will learn IT support and build competency in IT fundam"])</script><script>self.__next_f.push([1,"entals topics, including hardware, operating systems, software, system administration, programming, databases, networking, cybersecurity, and cloud computing, as well as critical skills covered such as customer service and troubleshooting. Mastery of these skills is essential for IT Helpdesk Support and also provides multiple options to grow your career as they are required skills for many technology jobs, including Software Engineer, Data Analyst, and Data Scientist.\u003c/p\u003e\r\n \r\n\u003cp\u003eThis Professional Certificate program from IBM is built by experts to prepare you for an entry-level job in Technical Support. If you can dedicate a few hours per week, you can complete the program in 3 to 6 months. By the end of the program, you will be equipped with job-ready skills employers look for, whether you are just starting out your IT career or changing jobs.\u003c/p\u003e\r\n\r\n\u003cp\u003eWhen you successfully complete the program you’ll receive dual credentials, IBM Digital Badges for each course to help your profile stand out, as well as a Professional Certificate to showcase your job readiness to potential employers.\u003c/p\u003e3b0:T9cb,"])</script><script>self.__next_f.push([1,"\u003cp\u003eArtificial Intelligence (AI) and Machine Learning (ML) now impact every aspect of our daily lives and routines - whether in the workplace or at home. This program introduces you into this exciting and disruptive technology and arms you with applied AI skills.\u003c/p\u003e\r\n\r\n\u003cp\u003eML is fast-developing, disruptive, and sometimes controversial, but anyone can benefit from a guided tour of how the technology works, its benefits and drawbacks, along with its implications for society.\u003c/p\u003e \r\n\r\n\u003cp\u003eThis program is intended to cut through the hype, help you understand what AI really is, and what it isn’t. It covers why data is important and demonstrates the relationship between data, machine learning, and artificial intelligence to help you discuss and use these technologies with others.\u003c/p\u003e\r\n \r\n\u003cp\u003eThe program kicks off with a Google AI for Anyone course that covers the basics of AI and ML and how AI is used in the real world. Learning from Google AI experts and practitioners, you will explore what machine learning programming looks like at a high level learning techniques such as neural networks. Later in the course you'll acquire some hands-on experience teaching a computer to recognize images, sounds, and more.\u003c/p\u003e\r\n\r\n\u003cp\u003eThe second course Google AI for JavaScript developers with TensorFlow.js builds upon the concepts introduced in course 1 but is still beginner friendly - you just need a basic knowledge of JavaScript, HTML, and CSS.\u003c/p\u003e \r\n\r\n\u003cp\u003eLearn how to give your web application superpowers to stand out from the crowd and create next generation web apps that can be used by billions of people in a single click - from computer vision to natural language processing.\u003c/p\u003e\r\n\r\n\u003cp\u003eYou'll learn how to use TensorFlow.js models and their APIs to create real working systems that solve problems that could impact real business ideas. Imagine offering a customer the ability to automatically block spam comments in a chat application or blog before they are even sent, or use state of the art models to build your very own smart security camera, and more.\u003c/p\u003e \r\n\r\n\u003cp\u003eBy leveraging TensorFlow.js - Google's open-source leading ML library for JavaScript - you will go deeper, learn how to use state of the art pre-made models, retrain existing models, and even take your first steps writing your own models to solve simple tasks taking your first steps as a Web Machine Learning Engineer.\u003c/p\u003e\r\n\r\n\u003cp\u003eKick off your Web AI and ML journey with this professional certificate program from Google today.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"3b1: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,"3b2: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,"3b3:Tc21,"])</script><script>self.__next_f.push([1,"\u003cp\u003eEmbedded systems engineers are in demand, thanks to the emergence of disruptive technologies like Artificial Intelligence (AI) and the 5G powered Internet of Things (IoT). What’s more, embedded systems are the building blocks of our connected world and Arm-based technologies are the industry standard. Any aspiring engineer looking to unlock the limitless potential of the Fifth Wave of Computing will need to have a fundamental understanding of this important subject area.\u003c/p\u003e \r\n\r\n\u003cp\u003eThe Arm EducationX Embedded Systems Essential Program will provide you with the foundational skills required to begin your embedded systems design and programming career. It is aimed at those familiar \u003cb\u003ewith computer or electrical engineering\u003c/b\u003e principles at an undergraduate level and with a basic understanding of a programming language such as C/C++.\u003c/p\u003e\r\n\r\n\u003cp\u003eWith over 180 billion Arm-based chips shipped to date, and a record 6.7 billion Cortex-M processors shipped in the fourth quarter of 2020, Arm continues to play a leading role in the development and popularisation of \u003cb\u003eembedded devices\u003c/b\u003e. If you’re looking to level-up your skills in this area, then this Program is the ideal place to begin your learning journey.\u003c/p\u003e \r\n\r\n\u003cp\u003eIn Part 1 of the Program, we’ll give you an overview of the characteristics of an embedded system – its components, benefits and constraints. All of this will be supported by Arm’s Mbed API – you can download and use the Mbed simulator on your own computer to quickly get started with \u003cb\u003eprototyping\u003c/b\u003e and building your \u003cb\u003emicrocontroller\u003c/b\u003e projects without the need for hardware.\r\n\r\n\u003cp\u003eYou’ll then apply your new knowledge of digital and analog I/O, interrupts, low power features, timer and pulse width modulation to program an audio wave generator and audio player, and control peripherals along the way.\u003c/p\u003e\r\n\r\n\u003cp\u003ePart 2 of the Program will build upon the knowledge acquired in the first course and combine this with new foundational skills focusing on Real-Time Operating Systems (RTOS) and Serial Communication as they’re applied to \u003cb\u003eArm Cortex-M microcontrollers\u003c/b\u003e. During the course, we’ll introduce you to practical lab exercises using the popular and affordable \u003cb\u003eST Nucleo F401RE\u003c/b\u003e board, enabling you to obtain real-world experience in implementing these key concepts, We’ve partnered with ST Microelectronics to ensure you get easy access to all the materials you’ll need to build your hardware-based embedded systems applications. Visit our course page to find out more.\u003c/p\u003e\r\n\r\n\u003cp\u003eWe’ll show you how to create applications including a user interface, temperature sensing system and a music player – with ideas to develop each further. By the end of the course, you’ll have an understanding of how to develop your own embedded systems application on industry-standard, Arm-based hardware.\u003c/p\u003e\r\n\r\n\u003cp\u003eThe world of embedded systems is your door into IoT, and all the opportunities it has to offer. Kickstart your embedded systems career by enrolling in the Arm EducationX Embedded Systems Essential Program.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"3b4: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,"3b5:Ta40,"])</script><script>self.__next_f.push([1,"\u003cp\u003eIn this program, you will learn about more advanced attacks in the space of side-channel security: transient-execution attacks and fault attacks. In the first course. we will focus on transient execution (and speculative execution) and how it can introduce data (not meta-data!) leakage. We will use side channels to exfiltrate data and transmit it to an attacker-controlled application. We will learn about the most prominent of transient-execution attacks: Meltdown, Spectre, Foreshadow, and ZombieLoad. These attacks are so powerful that they can leak arbitrary secret data, including cryptographic keys, all without physical access. In a set of small exercises, you will implement some of these attacks. You will understand the connection between these attacks and side-channel attacks. You will gain deep understanding of the microarchitecture of modern processors, out-of-order execution pipelines, transient-execution attacks and potential mitigations against them.\u003c/p\u003e\r\n\r\n\u003cP\u003eIn the second course, we will then focus more on fault attacks, in particular Rowhammer and Plundervolt. These attacks go beyond leaking information but instead we will manipulate data. These fault injection mechanisms are triggered purely from software and allows us to manipulate control flow, secret keys, and system security mechanisms, to fully subvert systems and bring them under our control. You will understand how these attacks can be mounted, and how they can be mitigated to allow you to develop hardware and software resilient to transient-execution and fault attacks. As an advanced topic in this block, we will also mount software-based differential power analysis attacks (DPA), following a similar methodology as for the physical side-channel attacks, leaking cryptographic keys. Again we will disucss what the countermeasures against these attacks are.\u003c/p\u003e\r\n\r\n\u003cp\u003eIn both courses, you will practically apply the acquired skills in simple exercises based on measurements you perform on your own computer or measurements we obtained from physical devices, that we provide to you. Both courses require programming skills (C, C++, Python). We will provide you with the knowledge required beyond these, including basics on operating systems, computer architecture, and hardware design.\u003c/p\u003e\r\n\r\n\u003cp\u003eDaniel Gruss is an internationally renowned expert in side-channel research and has written many seminal works in this field and presented them at renowned international conferences, especially on transient-execution attacks that affected the entire industry and defenses that have been implemented in all operating systems.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"3b6:T66e,\u003cp\u003eIn this program, you will learn about side channels in software and hardware. In software, we will focus on different types of caches, that are one of the main targets in software-based side-channel attacks.\u003c/p\u003e\r\n\r\n\u003cp\u003eOn the hardware side, we will mount power analysis attacks on the cryptographic algorithms RSA and AES. We will see that simple power analysis attacks and differential power analysis attacks are powerful enough to obtain fine-grained information such as cryptographic keys, user input, or secrets of the operating system. This skill set and knowledge will give you the ability to spot these side channels in hardware and software projects. We will then cover countermeasures and mitigation strategies that allow you to develop side-channel-resilient hardware and software and protect your security-critical applications and sensitive information.\u003c/p\u003e\r\n\r\n\u003cp\u003eIn both courses, you will practically apply the acquired skills in simple exercises based on measurements you perform on your own computer or measurements we obtained from physical devices, that we provide to you. Both courses require rudimentary programming skills (C, C++, Python). We will provide you with the knowledge required beyond these, including basics on operating systems, computer architecture, and hardware design.\u003c/p\u003e\r\n\r\n\u003cp\u003eDaniel Gruss is an internationally renowned expert in side-channel research and has written many seminal works in this field and presented them at renowned international conferences, especially on transient-execution attacks that affected the entire industry and defenses that have been implemented in all operating systems.\u003c/p\u003e3b7:T78d,\u003cp\u003eSide channels are everywhere. They allow attackers to steal secret information that is protected and never directly exposed to the attacker. They are incredibly powerful and have disrupted the world in the last years, especially with attacks like Meltdown and Spectre that impacted most computers on the planet. You have also likely seen side channels and used them already yours"])</script><script>self.__next_f.push([1,"elf.\u003c/p\u003e\r\n \r\n\u003cp\u003eIn this program, consisting of two courses, you will learn and practice the side-channel mindset , understand how to spot side channels in the real-world and how to use them in non-technical and semi-technical settings. The first course will provide you with the ability to spot side channels and the security problems they introduce in your job, research, studies, and in everyday life. In both courses, you will solve simple exercises using side channels in the real world and on computer systems to practically apply the acquired skills.\u003c/p\u003e\r\n\r\n\u003cp\u003eThe first course requires no programming skills and has an entirely web-based exercise. In the second course, you will need basic programming skills (reading C code is required). We will provide you with all basics beyond that, including basics on operating systems, computer architecture, cryptography, and most importantly side-channel analysis. You will learn and practice how basic software-based side channels work and how you can mitigate them to protect yourself as well as the hardware and software you develop. We will provide you with Docker containers (and a tutorial on how to use them), to run the exercises on your own computer.\u003c/p\u003e\r\n \r\n\u003cp\u003eDaniel Gruss is a internationally renowned expert in side-channel research and has written many seminal works in this field and presented them at renowned international conferences, especially on transient-execution attacks that affected the entire industry and defenses that have been implemented in all operating systems.\u003c/p\u003e3b8:T9d7,"])</script><script>self.__next_f.push([1,"\u003cp\u003eEmbedded systems are everywhere – and Arm-based technologies are the industry standard. Getting started could not be easier. This course includes instructions on how to access to an Mbed simulator (refer to the prerequisites section for more details) so you can apply your new knowledge and skills to prototype and build real-world embedded applications quickly, without the trouble or expense of sourcing hardware.\u003c/p\u003e\n\u003cp\u003eFrom the mobile, wearable, and smart devices of today to the transformative Artificial Intelligence (AI) and 5G powered Internet of Things (IoT) of the near future, embedded systems are the fundamental building blocks of our connected world. As we move from billions to trillions of intelligent, connected devices, it’s crucial that the next generation of engineers have a thorough understanding of how to rapidly build and deploy a modern embedded system solution.\u003c/p\u003e\n\u003cp\u003eIn this course, you will learn the fundamentals of an embedded system and discover why the Arm architecture and processors are particularly well suited for IoT applications.\u003c/p\u003e\n\u003cp\u003eOur interactive labs have been designed to cover the technical fundamentals, developing in-demand skills essential for any aspiring embedded systems engineer.\u003c/p\u003e\n\u003cp\u003eYou will begin by learning the characteristics of an embedded system, its components, benefits, and constraints, identify cost-performance trade-offs, and explore why the Arm architecture and processors are particularly well suited for the IoT.\u003c/p\u003e\n\u003cp\u003eYou will then apply your new knowledge of digital and analog I/O, interrupts, low power features, timer and pulse width modulation to program an audio wave generator and audio player, and control peripherals along the way.\u003c/p\u003e\n\u003cp\u003eAll of this will be supported by the Mbed API – so no additional hardware is required, you can download and use the simulator right on your own computer.\u003c/p\u003e\n\u003cp\u003eOver the six modules, you will gain a key overview of:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eEmbedded systems and their importance in modern computing applications\u003c/li\u003e\n\u003cli\u003eIndustry-standard Arm-based microcontroller architecture, their features and programming models.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe possibilities for future IoT development and connection are enormous. In order to achieve this vision of the future, many engineers and developers will be needed to imagine and design these connected devices and the technologies they are built on.\u003c/p\u003e\n\u003cp\u003eThe world of embedded systems is your doorway into the IoT, and all the opportunities it has to offer.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"3b9:T6d6,\u003cp\u003eThere is a growing interest in running software at the edge. This course takes a deep dive into the use cases and applications of Kubernetes at the edge using examples, labs, and a technical overview of the K3s project and the cloud native edge ecosystem.\u003c/p\u003e\n\u003cp\u003eThis course is designed for those interested learning more about Kubernetes, as well as in deploying applications or embedded sensors in edge locations. While learners do not need a Kubernetes certification for this course, experience with a Linux operating system and shell scripting will be beneficial. Programming experience is also not strictly required. Learners will need to be able to run Docker on their computer.\u003c/p\u003e\n\u003cp\u003eIn this course, you will learn the use cases for running compute in edge locations and about various supporting projects and foundations such as LF Edge and CNCF. The course covers how to deploy applications to the edge with open source tools such as K3s and k3sup, and how those tools can be applied to low-power hardware such as the Raspberry Pi. You will learn the challenges associated with edge compute, such as partial availability and the need for remote access. Through practical examples, students will gain experience of deploying applications to Kubernetes and get hands-on with object storage, MQTT and OpenFaaS. It also introduces the fleet management and GitOps models of deployment, and helps you understand messaging, and how to interface with sensors and real hardware.\u003c/p\u003e\n\u003cp\u003eThis course will enable developers to learn about the growing impact the cloud native movement is having on modernizing edge deployments. They will also learn the challenges of deploying Kubernetes on the edge through a concrete example via the k3s project.\u003c/p\u003e3ba:T60a,\u003cp\u003eThis course will introduce you to Linux, a powerful operating system used by most professional developers! \u003c/p\u003e\r\n\u003cp\u003eWhy add Linux to your C programming skills? Most people use Linux without knowing it! Whether you use a smartphone, search the web, or use an ATM, each time Linu"])</script><script>self.__next_f.push([1,"x is involved somewhere in the background. It is the most used operating system for embedded devices and high-performance servers. It is also the most common operating system used by developers to create software applications. \u003c/p\u003e\r\n\u003cp\u003eIn this course, you will learn the history of Linux and how its open source community was able to create today’s most advanced operating system. You will navigate the file system, use fundamental Linux commands and master the Linux command line interface. These are essential skills for every developer. \u003c/p\u003e\r\n\u003cp\u003eYou will also be able to produce software written in C using the industry-standard tools on Linux. \u003c/p\u003e\r\n\u003cp\u003eWithin moments you will be coding hands-on in a new browser tool developed for this course, receiving instant feedback on your code. No need to install anything! \u003c/p\u003e\r\n\u003cp\u003eWe are excited to introduce you to Linux and guide you along your path to becoming a skilled user of this powerful operating system! \u003c/p\u003e\r\n\u003cp\u003eAt the end of this short course, you will reach the sixth milestone of the C Programming with Linux” Professional Certificate program, unlocking the door to a career in computer engineering. \u003c/p\u003e\r\n\u003cp\u003eThis course has received financial support from the Patrick \u0026amp; Lina Drahi Foundation.\u003c/p\u003e3bb: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,"3bc:T576,\u003cp\u003eOn the hardware side, we will mount power analysis attacks on the cryptographic algorithms RSA and AES. We will see that simple power analysis attacks and differential power analysis attacks are powerful enough to obtain fine-grained information such as cryptographic keys, user input, or secrets of the operating system. This skill set and knowledge will give you the ability to spot these side channels in hardware and software projects. We will then cover countermeasures and mitigation strategies that allow you to develop side-channel-resilient hardware and software and protect your security-critical applications and sensitive information.\u003c/p\u003e\n\u003cp\u003eOn the software side, we will learn about branch prediction an prefetching. We will learn how these mechanisms can be subverted into powerful side-channel attacks. You will need programming skills (C, C++, Python) and we will provide you with the knowledge required beyond these, including basics on hardware design, computer architecture, operating systems, and cryptography.\u003c/p\u003e\n\u003cp\u003eYou will learn which attacks are relevant in the concrete environments you are working with, extending to your risk assessment skills. In a set of small exercises, you will demonstrate that you understood the techniques behind simple power analysis, and differential power analysis, as well as prefetch side channels and branch-prediction side channels.\u003c/p\u003e3bd: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 Jupyte"])</script><script>self.__next_f.push([1,"r 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 and 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\u003e3be: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,"3bf: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\u003e3c0:T8f7,"])</script><script>self.__next_f.push([1,"\u003cp\u003e\u003cstrong\u003eComing Soon February 2021.\u003c/strong\u003e Technological innovations have revolutionized the way we view and interact with the world around us. Editing a photo, re-mixing a song, automatically measuring and adjusting chemical concentrations in a tank: each of these tasks requires real-world data to be captured by a computer and then manipulated digitally to extract the salient information. Ever wonder how signals from the physical world are sampled, stored, and processed without losing the information required to make predictions and extract meaning from the data?\u003c/p\u003e\r\n\u003cp\u003eStudents will find out in this rigorous mathematical introduction to the engineering field of signal processing: the study of signals and systems that extract information from the world around us. This course will teach students to analyze discrete-time signals and systems in both the time and frequency domains. Students will learn convolution, discrete Fourier transforms, the z-transform, and digital filtering. Students will apply these concepts in interactive MATLAB programming exercises (all done in browser, no download required).\u003c/p\u003e\r\n\u003cp\u003eLearners should have strong problem solving skills, the ability to understand mathematical representations of physical systems, and advanced mathematical background (one-dimensional integration, matrices, vectors, basic linear algebra, imaginary numbers, and sum and series notation). This course is an excerpt from an advanced undergraduate class at Rice University taught to all electrical and computer engineering majors.\u003c/p\u003e\r\n\r\n\u003cp\u003e\u003cb\u003e\u003ca href=\"https://support.edx.org/hc/en-us/articles/360060426873-MicroBachelors-Coaching-FAQs\"\u003eCoaching\u003c/a\u003e\u003c/b\u003e\u003cbr\u003e\r\nIf you are enrolled in the verified track (paid track) in any course that is a part of a MicroBachelors program, including this course, you are eligible for \u003ci\u003ecoaching at no additional cost. Please note that coaching is only available via SMS to U.S. phone lines.\u003c/i\u003e\u003c/p\u003e\r\n\r\n\u003cp\u003eOur coaches (real humans) are ready to help you with career exploration, navigating resources, staying motivated, and solving problems along the way to your goals.\u003c/p\u003e\r\n\r\n\u003cp\u003eLearn more about the \u003ca href=\"https://www.youtube.com/watch?v=14QVCTJvHQo\u0026feature=youtu.be\"\u003evalue of coaching\u003c/a\u003e directly from one of our coaches, Erin.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"3c1: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. Access to a relatively recent x86 processor such as Intel Haswell or AMD Ryzen (or newer) running Linux is required. \u003c/p\u003e\n\u003cp\u003eMATLAB Online licenses will be made available to the participants free of charge for the duration of the course. \u003c/p\u003e\n\u003cp\u003eJoin us to satisfy your need for speed!\u003c/p\u003e3c2: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,"3c3:T45b,\u003cp\u003eQuantum computing is expected to impact all industries, ranging from cybersecurity to medicine. It provides a promise to solve many problems faster and more efficiently than classical computers. This course will introduce you to the core concepts related to quantum computing and give you an opportunity to explore IBM Q Experience Visual Composer. This graphical quantum programming tool lets you build quantum circuits and run them on real quantum hardware or simulators.\u003c/p\u003e\n\u003cp\u003eGeared towards anyone new to the field of quantum computing, this course is intended for a large audience, ranging from high school students to working professionals who do not have prior knowledge about quantum computing or those wishing to strengthen their foundational knowledge.\u003c/p\u003e\n\u003cp\u003eThis course discusses the basics of quantum computing. You will gain an understanding of the technology landscape—the present state and the future potential of quantum computing. You will also learn how to create quantum circuits for various quantum algorithms and be able to interact with quantum hardware using IBM Q Visual Composer.\u003c/p\u003e3c4: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 "])</script><script>self.__next_f.push([1,"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) 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\u003e3c5:T786,\u003cp\u003eThe Data Structures \u0026amp; Algorithms course begins with a review of some important Java techniques and nuances in programming. The course requires some prior knowledge of Java and object-oriented programming, but not in data structures or algorithms. This course introduces you to time complexity, and threads this concept throughout all data structures and algorithms presented in the course. You will work with the principles of data storage in Arrays and LinkedList nodes. You will program the low-level data structures: Singly, Circular and Doubly LinkedLists; and explore edge cases and efficiencies. LinkedLists and Arrays are used to implement Abstract Data Types, ADTs: Stacks, Queues and Deques. Harnessing the power of recursion to move through these data structures is necessary. As the size changes in your data structures, it becomes important to examine amortized analysis of the operations.\u003c/p\u003e\n\u003cp\u003eThe course design has several components and is built around modules. A module consists of a series of short (3-5 minute) instructional videos. In between the videos, there are textual frames with additional content information for clarification, as well as video errata dropdown boxes. All modules include an Exploratory Lab that incorporates a Visualiz"])</script><script>self.__next_f.push([1,"ation Tool specifically designed for this course. The lab includes discovery questions that lead you towards delving deeper into the efficiency of the data structures and examining the edge cases. This is followed by a set of comprehension questions on topics covered in the module that count for 10% of your grade. The modules end with Java coding assignments which are 60% of your grade. Lastly, you'll complete a course exam, which counts for the remaining 30% of your grade.\u003c/p\u003e\n\u003cp\u003eThis is a great course that has been derived from the on-campus version of CS1332 at the Georgia Institute of Technology, and is backed with an impressive reputation.\u003c/p\u003e3c6:T96e,"])</script><script>self.__next_f.push([1,"\u003cp\u003eThis Data Structures \u0026amp; Algorithms course extends beyond linear data structures in CS1332xI to the nonlinear and hierarchical data structures here in CS1332xII. A short Java review is presented on topics relevant to new data structures covered in this course. The course does require prior knowledge of Java, object-oriented programming and linear data structures. Time complexity is threaded throughout the course within all the nonlinear data structures and algorithms.\u003c/p\u003e\n\u003cp\u003eYou will explore the hierarchical data structure of trees. Trees have important properties such as shape and order which are used to categorize trees into different groups and define their functionality. The course begins by explaining Binary Trees and two subgroups: Binary Search Trees (BSTs) and Binary Heaps. You will program BSTs, their operations and traversal algorithms. BSTs are an important structure when wanting to access information quickly. Heaps approach access differently and prioritize what data is accessed. Heaps also employ the concept of up-heap and down-heap operations not found in other structures.\u003c/p\u003e\n\u003cp\u003eHashMaps and SkipLists are the last data structures discussed in the course. The HashMap ADT is a collection of key-value pairs. The key-value pairs are stored in an unordered manner based on hash codes and compression functions that translate keys into integers. You will investigate different collision strategies and implement one. SkipLists are a probabilistic data structures where data is placed in the structure based on a randomization procedure.\u003c/p\u003e\n\u003cp\u003eThe course design has several components and is built around modules. A module consists of a series of short (3-5 minute) instructional videos. In between the videos, there are textual frames with additional content information for clarification, as well as video errata dropdown boxes. All modules include an Exploratory Lab that incorporates a Visualization Tool specifically designed for this course. The lab includes discovery questions that lead you towards delving deeper into the efficiency of the data structures and examining the edge cases. This is followed by a set of comprehension questions on topics covered in the module that count for 10% of your grade. The modules end with Java coding assignments which are 60% of your grade. Lastly, you'll complete a course exam, which counts for the remaining 30% of your grade.\u003c/p\u003e"])</script><script>self.__next_f.push([1,"3c7:T466,\u003cp\u003eThis course gives you a thorough introduction to the python programming language. You'll start by learning the definition of python, its history, semantics, and how it works. The first week concludes by writing a python script to solve a problem. In Week 2, you'll learn about Serverless Architectures and understand the differences between microservices, service-oriented and monolith architectures. You'll build a microservices architecture by learning how to use the following tools: AWS Lambda, Amazon API Gateway, and Cloud9. It's then time to go deep with AWS Databases. You'll see Amazon RDS and Amazon DynamoDB in action, visualizing the important role they play in developing applications in python. The course's final week will cover application integration services. Amazon's Simple Notification Service (SQS), Simple Queue Service (SQS), and EventBridge take center stage as important “glue” components for scalable, cloud-based applications. You'll close the course with a hands-on project, writing some code to use some hardcoded data to write to dynamodb and then convert that into a lambda function.\u003c/p\u003e3c8:T83a,"])</script><script>self.__next_f.push([1,"\u003cp\u003eThis course is part III of the series of Quantum computing courses, which covers aspects from fundamentals to present-day hardware platforms to quantum software and programming.\u003c/p\u003e\n\u003cp\u003eThe goal of part III is to discuss some of the key domain-specific algorithms that are developed by exploiting the fundamental quantum phenomena (e.g. entanglement)and computing models discussed in part I. We will begin by discussing classic examples of quantum Fourier transform and search algorithms, along with its application for factorization (the famous Shor’s algorithm). Next, we will focus on the more recently developed algorithms focusing on applications to optimization, quantum simulation, quantum chemistry, machine learning, and data science.\u003c/p\u003e\n\u003cp\u003eA particularly exciting recent development has been the emergence of near-intermediate scale quantum (NISQ) computers. We will also discuss how these machines are driving new algorithmic development. A key aspect of the course is to provide hands-on training for running (few qubit instances of) the quantum algorithms on present-day quantum hardware. 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,"3c9:T42d,\u003cp\u003eMachine learning is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. This area is also concerned with issues both theoretical and practical.\u003c/p\u003e\r\n\u003cp\u003eIn this course, we will present algorithms and approaches in such a way that grounds them in larger systems as you learn about a variety of topics, including:\u003c/p\u003e\r\n\u003cul\u003e\r\n\u003cli\u003estatistical supervised and unsupervised learning methods\u003c/li\u003e\r\n\u003cli\u003erandomized search algorithms\u003c/li\u003e\r\n\u003cli\u003eBayesian learning methods\u003c/li\u003e\r\n\u003cli\u003ereinforcement learning\u003c/li\u003e\r\n\u003c/ul\u003e\r\n\u003cp\u003eThe course also covers theoretical concepts such as inductive bias, the PAC and Mistake‐bound learning frameworks, minimum description length principle, and Ockham's Razor. In order to ground these methods the course includes some programming and involvement in a number of projects.\u003c/p\u003e\r\n\u003cp\u003eBy the end of this course, you should have a strong understanding of machine learning so that you can pursue any further and more advanced learning.\u003c/p\u003e\r\n\u003cp\u003eThis is a three-credit course.\u003c/p\u003e3ca:T45c,\u003cp\u003eData Science techniques are very powerful predictive tools for all types of organizations. Recent advancements in data collection, data science libraries and more powerful computers have put advanced data science within reach of all size organizations.\u003c/p\u003e \r\n\r\n\u003cp\u003eThis series of courses uses easy to learn, state of the art, free tools of Python, Scikit-Learn and Tableau to perform advanced data science. Most examples use real dataset so the skills that you are learning produce real results.\u003c/p\u003e \r\n\r\n\u003cp\u003eCourses cover numerous useful topics. Data preprocessing shows students how to easily normalize data and how domain space reduction can improve results. Supervised Learning algorithms like K-Nearest Neighbor, Regression, Decision Tree and Random Forest are covered. Unsupervised Learning algorithms like K-means, DBSCAN and Hierarchical clustering are also covered. Tableau is used to show students how to visualize data.\u003c/p\u003e \r\n\r\n\u003cp\u003eThese courses"])</script><script>self.__next_f.push([1," do require basic programming skills, except for the Data Visualization course. The Data Visualization course has no prerequisite skills requirements.\u003c/p\u003e3cb:T564,\u003cp\u003eQuesto corso si occupa della programmazione orientata agli oggetti (classi, oggetti, ereditarietà, polimorfismo, le altre relazioni tra classi), la memoria dinamica, lo sviluppo di alcuni contenitori quali pile e code, la gestione delle eccezioni. \u003c/p\u003e\n\u003cp\u003eImparerai a progettare un algoritmo e i concetti fondamentali di programmazione utilizzando come linguaggio di riferimento il linguaggio C++. Per sviluppare gli esempi e gli esercizi presentati durante il corso è possibile utilizzare un qualsiasi compilatore C++ (Standard). Si segnalano: l'ambiente di sviluppo DevC++ (GNU General Public License) per Windows, Xcode per Mac OS X, il compilatore GNU C++ su Linux, l'ambiente C++ per piattaforma Eclipse. \u003c/p\u003e\n\u003cp\u003eThe aim of this course is to illustrate the object-oriented programming (classes, objects, inheritance, polymorphism and other relationships between classes), the dynamic memory, the development of other containers such as piles and queues and the management of the exceptions. \u003c/p\u003e\n\u003cp\u003eMoreover, the students will learn how to design algorithms and other fundamental programming concepts in C++ language. All the examples and exercises of this course can be developed with any C++ (Standard) compiler: the environment development DevC++ (GNU General Public License) for Windows, Xcode for Mac OS X, GNU C++ for Linux and the environment C++ for Eclipse.\u003c/p\u003e3cc:T72a,\u003cp\u003eA self-contained course on the fundamentals of modern optimization with equal emphasis on theory, implementation, and application. We consider linear and nonlinear optimization problems, as well as closely related fields such as network flow models and game-theoretic models in which selfish agents compete for shared resources. We apply these models to real-world scenarios such as routing problems in urban railway management.\u003c/p\u003e\n\u003cp\u003eThe first four weeks of the course consider linear progr"])</script><script>self.__next_f.push([1,"amming (LP). LP is the most fundamental example of convex programming. Despite its simplicity, a wide range of practical problems can be formulated using LP, and LPs can be solved using efficient algorithms, meaning that LP is of both theoretical and practical importance. We highlight this point in week 3, when we examine the relation between the duality theories of LP and classic problems in game theory, such as the minimax theorem, and study the relationship between solving optimization problems and predicting how rational agents participate in competitive games. In week 4, we explore the minimum cost flow problem, a fundamental network model, and how the simplex method can be tailored to its unique features. Weeks 5 through 7 consider nonlinear, especially convex, optimization problems, also known as nonlinear programs (NLP). We derive the optimality criteria for NLP, and through them understand the connection between LP and NLP. We look at a variety of solution algorithms for NLPs with and without constraints.\u003c/p\u003e\n\u003cp\u003eFinally, in week 8, we put everything together to solve a game-theoretic problem called the routing problem. We simulate a modern subway system, with selfish agents who compete to minimize their travel costs, and use this model to predict the impact of new railway construction on train congestion.\u003c/p\u003e3cd: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 po"])</script><script>self.__next_f.push([1,"tential 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\u003e3ce:T62c,\u003cp\u003eThe metaverse. The “internet of things.” Augmented reality. Automation. Driverless cars. Robotics. Enhanced security and modeling. These are just a few of the innovations, technologies, and trends in which companies are investing as they prepare for a more tech-forward future. And they’re all powered by artificial intelligence (AI) and related tools and concepts. \u003c/p\u003e\r\n\r\n\u003cp\u003eThere are boundless opportunities to discover in AI. In fact, LinkedIn listed AI practitioners among its top 15 “Jobs on the Rise” for 2021.* Yet even as this field is set to expand dramatically, experts project a shortage of qualified AI professionals and practitioners — a talent gap that some firms worry could potentially slow innovation and lead to other unexpected issues.** Businesses and organizations operating in the field need brave AI practitioners and experts to step up and take the lead. \u003c/p\u003e\r\n\r\n\u003cp\u003eWith your 100% online Master of Science in Artificial Intelligence from Maryville University, you can help meet that need as you prepare to thrive in "])</script><script>self.__next_f.push([1,"the future of AI. Maryville is a leader in tech-forward, future-focused education, and we’re here to help you learn the concepts and techniques to develop and operate state-of-the-art artificial intelligence and machine learning tools, apply critical thinking and leadership skills, and help build a more technologically advanced world. \u003c/p\u003e\r\n\r\n\u003cp\u003e*LinkedIn, “LinkedIn Jobs on the Rise: 15 opportunities that are in demand and hiring now” \u003c/p\u003e\r\n\r\n\u003cp\u003e**The Hill, “The reality of America’s AI talent shortages”\u003c/p\u003e3cf:T499,In today's dynamic business landscape, data-driven decision-making is key. That's why we've designed a skills-based learning program that not only equips you with the latest analytics tools and techniques 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.3d0: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"])</script><script>self.__next_f.push([1,". 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.3d1: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,"3d2:Ta6f,"])</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 Applied Mathematics degree, students learn mathematical theories and modeling techniques and apply them to solve real-world problems in various fields. The curriculum typically includes courses in calculus, linear algebra, differential equations, probability theory, statistics, numerical analysis, and optimization. The degree program includes projects, research opportunities, and internships, and students may also study advanced topics in mathematics.\n-Calculus: Students learn calculus, including differentiation and integration, which is used to model real-world problems and analyze changes in physical and mathematical systems.\n-Linear algebra: Students learn linear algebra, including matrix algebra and eigenvalue analysis, which is used to solve systems of linear equations and in data analysis.\n-Differential equations: Students learn differential equations, which are used to model physical phenomena and systems that change over time.\n-Probability theory: Students learn probability theory, including random variables and distributions, which is used in data analysis and modeling of random phenomena.\n-Statistics: Students learn statistical methods and techniques, including regression analysis, hypothesis testing, and sampling theory, which are used in data analysis and empirical research.\n-Numerical analysis: Students learn numerical methods for solving mathematical problems that are difficult or impossible to solve analytically, such as systems of differential equations or optimization problems.\n-Optimization: Students learn optimization techniques, including linear and nonlinear programming, which are used to solve problems and model decision-making in various fields.\n-Mathematical modeling: Students learn how to model real-world problems using mathematical tools and techniques, and how to interpret and communicate the results.\n-Computer programming: Students learn computer programming and algorithm design, which is used to solve mathematical problems and implement numerical methods.\n-Advanced topics: Students may study advanced topics in mathematics, such as abstract algebra, topology, real analysis, and partial differential equations, to gain a deeper understanding of mathematical theories and applications."])</script><script>self.__next_f.push([1,"3d3: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.3d4: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"])</script><script>self.__next_f.push([1," 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.3d5:Ta16,"])</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 Applied Mathematics degree, students learn mathematical theories and modeling techniques and apply them to solve real-world problems in various fields. The curriculum typically includes courses in calculus, linear algebra, differential equations, probability theory, statistics, numerical analysis, and optimization. The degree program includes projects, research opportunities, and internships, and students may also study advanced topics in mathematics.\n-Calculus: Students learn calculus, including differentiation and integration, which is used to model real-world problems and analyze changes in physical and mathematical systems.\n-Linear algebra: Students learn linear algebra, including matrix algebra and eigenvalue analysis, which is used to solve systems of linear equations and in data analysis.\n-Differential equations: Students learn differential equations, which are used to model physical phenomena and systems that change over time.\n-Probability theory: Students learn probability theory, including random variables and distributions, which is used in data analysis and modeling of random phenomena.\n-Statistics: Students learn statistical methods and techniques, including regression analysis, hypothesis testing, and sampling theory, which are used in data analysis and empirical research.\n-Numerical analysis: Students learn numerical methods for solving mathematical problems that are difficult or impossible to solve analytically, such as systems of differential equations or optimization problems.\n-Optimization: Students learn optimization techniques, including linear and nonlinear programming, which are used to solve problems and model decision-making in various fields.\n-Mathematical modeling: Students learn how to model real-world problems using mathematical tools and techniques, and how to interpret and communicate the results.\n-Computer programming: Students learn computer programming and algorithm design, which is used to solve mathematical problems and implement numerical methods.\n-Advanced topics: Students may study advanced topics in mathematics, such as abstract algebra, topology, real analysis, and partial differential equations, to gain a deeper understanding of mathematical theories and applications."])</script><script>self.__next_f.push([1,"3d6:T9a9,"])</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 Applied Mathematics degree, students learn mathematical theories and modeling techniques and apply them to solve real-world problems in various fields. The curriculum typically includes courses in calculus, linear algebra, differential equations, probability theory, statistics, numerical analysis, and optimization. The degree program includes projects, research opportunities, and internships, and students may also study advanced topics in mathematics.\n-Calculus: Students learn calculus, including differentiation and integration, which is used to model real-world problems and analyze changes in physical and mathematical systems.\n-Linear algebra: Students learn linear algebra, including matrix algebra and eigenvalue analysis, which is used to solve systems of linear equations and in data analysis.\n-Differential equations: Students learn differential equations, which are used to model physical phenomena and systems that change over time.\n-Probability theory: Students learn probability theory, including random variables and distributions, which is used in data analysis and modeling of random phenomena.\n-Statistics: Students learn statistical methods and techniques, including regression analysis, hypothesis testing, and sampling theory, which are used in data analysis and empirical research.\n-Numerical analysis: Students learn numerical methods for solving mathematical problems that are difficult or impossible to solve analytically, such as systems of differential equations or optimization problems.\n-Optimization: Students learn optimization techniques, including linear and nonlinear programming, which are used to solve problems and model decision-making in various fields.\n-Mathematical modeling: Students learn how to model real-world problems using mathematical tools and techniques, and how to interpret and communicate the results.\n-Computer programming: Students learn computer programming and algorithm design, which is used to solve mathematical problems and implement numerical methods.\n-Advanced topics: Students may study advanced topics in mathematics, such as abstract algebra, topology, real analysis, and partial differential equations, to gain a deeper understanding of mathematical theories and applications."])</script><script>self.__next_f.push([1,"3d7: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 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.3d8: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 ma"])</script><script>self.__next_f.push([1,"nagement, 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 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.3d9: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 a"])</script><script>self.__next_f.push([1,"rguments.\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.3da:T67f,- #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-An undergraduate degree in Statistics teaches students the principles of statistical theory and methods, including probability theory, data analysis, and statistical inference.\n-Students learn how to design experiments and studies, collect and analyze data, and draw conclusions from statistical analysis.\n-They study statistical modeling and regression analysis, using mathematical and statistical tools to model relationships between variables.\n-Statistics students develop skills in data visualization and communication, including graphing, charting, and presenting data.\n-They learn about the applications of statistics in fields such as biology, economics, psychology, and public health.\n-Students study the "])</script><script>self.__next_f.push([1,"principles of machine learning and data mining, using statistical and computational methods to analyze large datasets.\n-Statistics students learn how to use statistical software and computer programming languages to solve statistical problems and analyze data.\n-They also study the history and philosophy of statistics, exploring the development of statistical ideas and their relationship to other fields of study.\n-Statistics students learn how to communicate statistical ideas and findings through technical writing and presentations.\n-Finally, an undergraduate degree in 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.3db: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"])</script><script>self.__next_f.push([1," 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.3dc: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+ 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 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 Informatio"])</script><script>self.__next_f.push([1,"n 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.3dd: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 Details3de: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,"3df: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,"3e0: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,"3e1: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,"3e2: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,"3e3: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,"3e4: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,"3e5: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,"3e6: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,"3e7: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,"3e8: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,"3e9: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,"3ea: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,"3eb: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,"3ec: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,"3ed: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. 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