Course Catalog: Data Science | UC Berkeley School of Information

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<div class="tbm-column-inner"> <ul class="tbm-subnav level-2 items-2" role="list"> <li class="tbm-item level-3" aria-level="3" data-id="6620" > <div class="tbm-link-container"> <a href="/programs/5th-year-mids/careers" class="tbm-link level-3" title="5th Year MIDS Career Outcomes and ROI"> Career Outcomes </a> </div> </li> <li class="tbm-item level-3" aria-level="3" data-id="8140" > <div class="tbm-link-container"> <a href="/programs/5th-year-mids/capstone" class="tbm-link level-3"> Capstone Project </a> </div> </li> </ul> </div> </div> </div> </div> </div></div> </li> </ul> </div> </div> <div class="tbm-column span3"> <div class="tbm-column-inner"> <ul class="tbm-subnav level-1 items-2" role="list"> <li class="tbm-item level-2 tbm-group" aria-level="2" data-id="858" > <div class="tbm-link-container"> <a href="/programs/mids" class="tbm-link level-2 tbm-group-title" title="Master of Information & Data Science" aria-expanded="false"> MIDS Program </a> </div> <div class="tbm-group-container tbm-item-child" role="list"><div class="dropdown-menu-inner"> <div class="mega-dropdown-inner"> <div class="tbm-row"> <div class="tbm-column span12"> <div class="tbm-column-inner"> <ul class="tbm-subnav level-2 items-7" role="list"> <li class="tbm-item level-3" aria-level="3" data-id="2247" > <div class="tbm-link-container"> <a href="https://ischoolonline.berkeley.edu/admissions/" class="tbm-link level-3" title="How to apply to the Master of Information & Data Science degree program" target="_blank"> Admissions </a> </div> </li> <li class="tbm-item level-3" aria-level="3" data-id="6656" > <div class="tbm-link-container"> <a href="/programs/mids/larson-fellowship" class="tbm-link level-3" title="The Data for Good fellowship supports MIDS students who desire to use data science to benefit society."> Jack Larson Data for Good Fellowship </a> </div> </li> <li class="tbm-item level-3" aria-level="3" data-id="9408" > <div class="tbm-link-container"> <a href="/programs/mids/tuition" class="tbm-link level-3"> Tuition & Fees </a> </div> </li> <li class="tbm-item level-3" aria-level="3" data-id="2220" > <div class="tbm-link-container"> <a href="/programs/mids/capstone" class="tbm-link level-3" title="Capstone projects are the culmination of of the Master of Information & Data Science program"> Capstone Project </a> </div> </li> <li class="tbm-item level-3 hide-submenu" aria-level="3" data-id="4930" > <div class="tbm-link-container"> <a href="/programs/mids/women" class="tbm-link level-3"> Women in MIDS </a> </div> </li> <li class="tbm-item level-3" aria-level="3" data-id="8620" > <div class="tbm-link-container"> <a href="/programs/mids/news" class="tbm-link level-3"> MIDS Curriculum News </a> </div> </li> <li class="tbm-item level-3" aria-level="3" data-id="8585" > <div class="tbm-link-container"> <a href="https://ischoolonline.berkeley.edu/form-data-science/" class="tbm-link level-3" target="_blank"> Request Information </a> </div> </li> </ul> </div> </div> </div> </div> </div></div> </li> <li class="tbm-item level-2 tbm-group" aria-level="2" data-id="4927" > <div class="tbm-link-container"> <a href="/programs/mics" class="tbm-link level-2 tbm-group-title" title="Master of Information and Cybersecurity" aria-expanded="false"> MICS Program </a> </div> <div class="tbm-group-container tbm-item-child" role="list"><div class="dropdown-menu-inner"> <div class="mega-dropdown-inner"> <div class="tbm-row"> <div class="tbm-column span12"> <div class="tbm-column-inner"> <ul class="tbm-subnav level-2 items-5" role="list"> <li class="tbm-item level-3" aria-level="3" data-id="6891" > <div class="tbm-link-container"> <a href="https://ischoolonline.berkeley.edu/admissions/" class="tbm-link level-3" target="_blank"> Admissions </a> </div> </li> <li class="tbm-item level-3" aria-level="3" data-id="8975" > <div class="tbm-link-container"> <a href="/news/mics" class="tbm-link level-3"> MICS Student News </a> </div> </li> <li class="tbm-item level-3" aria-level="3" data-id="9409" > <div class="tbm-link-container"> <a href="/programs/mics/tuition" class="tbm-link level-3"> Tuition & Fees </a> </div> </li> <li class="tbm-item level-3" aria-level="3" data-id="6889" > <div class="tbm-link-container"> <a href="/programs/mics/capstone" class="tbm-link level-3"> Capstone Project </a> </div> </li> <li class="tbm-item level-3" aria-level="3" data-id="8586" > <div class="tbm-link-container"> <a href="https://ischoolonline.berkeley.edu/form-cybersecurity/" class="tbm-link level-3" target="_blank"> Request Information </a> </div> </li> </ul> </div> </div> </div> </div> </div></div> </li> </ul> </div> </div> <div class="tbm-column span3"> <div class="tbm-column-inner"> <ul class="tbm-subnav level-1 items-3" role="list"> <li class="tbm-item level-2 tbm-group" aria-level="2" data-id="857" > <div class="tbm-link-container"> <a href="/programs/phd" class="tbm-link level-2 tbm-group-title" aria-expanded="false"> Ph.D. Program </a> </div> <div class="tbm-group-container tbm-item-child" role="list"><div class="dropdown-menu-inner"> <div class="mega-dropdown-inner"> <div class="tbm-row"> <div class="tbm-column span12"> <div class="tbm-column-inner"> <ul class="tbm-subnav level-2 items-7" role="list"> <li class="tbm-item level-3 hide-submenu" aria-level="3" data-id="2246" > <div class="tbm-link-container"> <a href="/programs/phd/admissions" class="tbm-link level-3" title="How to apply to the Ph.D. program"> Admissions </a> </div> </li> <li class="tbm-item level-3" aria-level="3" data-id="6605" > <div class="tbm-link-container"> <a href="/programs/phd/careers" class="tbm-link level-3"> Career Outcomes </a> </div> </li> <li class="tbm-item level-3" aria-level="3" data-id="2216" > <div class="tbm-link-container"> <a href="/programs/phd/degreerequirements" class="tbm-link level-3"> Degree Requirements </a> </div> </li> <li class="tbm-item level-3" aria-level="3" data-id="8390" > <div class="tbm-link-container"> <a href="/programs/phd/funding" class="tbm-link level-3"> Funding Your Education </a> </div> </li> <li class="tbm-item level-3" aria-level="3" data-id="1085" > <div class="tbm-link-container"> <a href="/programs/phd/dissertations" class="tbm-link level-3"> Dissertations </a> </div> </li> <li class="tbm-item level-3" aria-level="3" data-id="2256" > <div class="tbm-link-container"> <a href="/programs/phd/events" class="tbm-link level-3"> Admissions Events </a> </div> </li> <li class="tbm-item level-3" aria-level="3" data-id="4631" > <div class="tbm-link-container"> <a href="/programs/phd/moreinfo" class="tbm-link level-3" title="Sign up for more information about our Ph.D. program"> Request Information </a> </div> </li> </ul> </div> </div> </div> </div> </div></div> </li> <li class="tbm-item level-2 tbm-group" aria-level="2" data-id="7133" > <div class="tbm-link-container"> <a href="/programs/certificates" class="tbm-link level-2 tbm-group-title" aria-expanded="false"> Graduate Certificates </a> </div> <div class="tbm-group-container tbm-item-child" role="list"><div class="dropdown-menu-inner"> <div class="mega-dropdown-inner"> <div class="tbm-row"> <div class="tbm-column span12"> <div class="tbm-column-inner"> <ul class="tbm-subnav level-2 items-2" role="list"> <li class="tbm-item level-3 hide-submenu" aria-level="3" data-id="6786" > <div class="tbm-link-container"> <a href="/programs/data-science-certificate" class="tbm-link level-3"> Applied Data Science Certificate </a> </div> </li> <li class="tbm-item level-3 hide-submenu" aria-level="3" data-id="860" > <div class="tbm-link-container"> <a href="/programs/ictd" class="tbm-link level-3"> ICTD Certificate </a> </div> </li> </ul> </div> </div> </div> </div> </div></div> </li> <li class="tbm-item level-2 hide-submenu" aria-level="2" data-id="8976" > <div class="tbm-link-container"> <a href="/programs/cybersecurityclinic" class="tbm-link level-2"> Cybersecurity Clinic </a> </div> </li> </ul> </div> </div> <div class="tbm-column span3"> <div class="tbm-column-inner"> <div class="tbm-block"> <div class="block-inner"> <div id="block-block-content953e713f-cec1-4e84-a942-39a02dbb7ffb" class="block block-block-content block-block-content953e713f-cec1-4e84-a942-39a02dbb7ffb"> <div class="content"> <div class="clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item"><p>The School of Information offers four degrees:</p><p>The <a href="/programs/mims"><strong>Master of Information Management and Systems (MIMS)</strong></a> program educates information professionals to provide leadership for an information-driven world.</p><p>The <a href="https://ischoolonline.berkeley.edu/data-science/"><strong>Master of Information and Data Science (MIDS)</strong></a> is an online degree preparing data science professionals to solve real-world problems. The 5th Year MIDS program is a streamlined path to a MIDS degree for Cal undergraduates.</p><p>The <a href="https://ischoolonline.berkeley.edu/cybersecurity/"><strong>Master of Information and Cybersecurity (MICS)</strong></a> is an online degree preparing cybersecurity leaders for complex cybersecurity challenges.</p><p>Our <a href="/programs/phd"><strong>Ph.D. in Information Science</strong></a> is a research program for next-generation scholars of the information age.</p></div> </div> </div> </div> </div> </div> </div> </div> </div> </div></div> </li> <li class="tbm-item level-1 tbm-item--has-dropdown active active-trail" aria-level="1" data-id="555" > <div class="tbm-link-container"> <a href="/courses" class="tbm-link level-1 tbm-toggle active-trail" aria-expanded="false"> Courses </a> <button class="tbm-submenu-toggle"><span class="visually-hidden">Toggle submenu</span></button> </div> <div class="tbm-submenu tbm-item-child tbm-has-width" style="width: 1000px;" role="list"><div 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class="tbm-link level-3"> Fall 2024 Course Schedule </a> </div> </li> <li class="tbm-item level-3" aria-level="3" data-id="3017" > <div class="tbm-link-container"> <a href="/courses/info/2025/spring" class="tbm-link level-3" title="On-campus courses for the spring 2019 semester"> Spring 2025 Course Schedule </a> </div> </li> </ul> </div> </div> </div> </div> </div></div> </li> </ul> </div> </div> <div class="tbm-column span3"> <div class="tbm-column-inner"> <ul class="tbm-subnav level-1 items-1" role="list"> <li class="tbm-item level-2 tbm-group active active-trail" aria-level="2" data-id="1416" > <div class="tbm-link-container"> <a href="/courses/datasci" class="tbm-link level-2 tbm-group-title active-trail" aria-expanded="false"> Data Science Course Catalog </a> </div> <div class="tbm-group-container tbm-item-child" role="list"><div class="dropdown-menu-inner"> <div class="mega-dropdown-inner"> <div class="tbm-row"> <div class="tbm-column span12"> <div class="tbm-column-inner"> <ul class="tbm-subnav level-2 items-3" role="list"> <li class="tbm-item level-3" aria-level="3" data-id="2217" > <div class="tbm-link-container"> <a href="/courses/datasci/2024/fall" class="tbm-link level-3"> Fall 2024 Course Schedule </a> </div> </li> <li class="tbm-item level-3" aria-level="3" data-id="3929" > <div class="tbm-link-container"> <a href="/courses/datasci/2025/spring" class="tbm-link level-3"> Spring 2025 Course Schedule </a> </div> </li> </ul> </div> </div> </div> </div> </div></div> </li> </ul> </div> </div> <div class="tbm-column span3"> <div class="tbm-column-inner"> <ul class="tbm-subnav level-1 items-1" role="list"> <li class="tbm-item level-2 tbm-group" aria-level="2" data-id="5118" > <div class="tbm-link-container"> <a href="/courses/cyber" class="tbm-link level-2 tbm-group-title" aria-expanded="false"> Cybersecurity Course Catalog </a> </div> <div class="tbm-group-container tbm-item-child" role="list"><div class="dropdown-menu-inner"> <div class="mega-dropdown-inner"> <div class="tbm-row"> <div class="tbm-column span12"> <div class="tbm-column-inner"> <ul class="tbm-subnav level-2 items-3" role="list"> <li class="tbm-item level-3" aria-level="3" data-id="6049" > <div class="tbm-link-container"> <a href="/courses/cyber/2024/fall" class="tbm-link level-3" title="Online cybersecurity courses for the fall 2018 term"> Fall 2024 Course Schedule </a> </div> </li> <li class="tbm-item level-3" aria-level="3" data-id="6050" > <div class="tbm-link-container"> <a href="/courses/cyber/2025/spring" class="tbm-link level-3" title="Online cybersecurity courses for the spring 2019 term"> Spring 2025 Course Schedule </a> </div> </li> </ul> </div> </div> </div> </div> </div></div> </li> </ul> </div> </div> <div class="tbm-column span3"> <div class="tbm-column-inner"> <div class="tbm-block"> <div class="block-inner"> <div id="block-block-content94491d8f-75c0-4e0a-b123-cbba48b402cc" class="block block-block-content block-block-content94491d8f-75c0-4e0a-b123-cbba48b402cc"> <div class="content"> <div class="clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item"><p>The School of Information's courses bridge the disciplines of information and computer science, design, social sciences, management, law, and policy. We welcome interest in our graduate-level Information classes from current UC Berkeley graduate and undergraduate students and community members. <a href="/courses/take-a-class">More information about signing up for classes.</a></p></div> </div> </div> </div> </div> </div> </div> </div> </div> </div></div> </li> <li class="tbm-item level-1 tbm-item--has-dropdown" aria-level="1" data-id="773" > <div class="tbm-link-container"> <a href="/people" class="tbm-link level-1 tbm-toggle" aria-expanded="false"> People </a> <button class="tbm-submenu-toggle"><span class="visually-hidden">Toggle submenu</span></button> </div> <div class="tbm-submenu tbm-item-child tbm-has-width" style="width: 1000px;" role="list"><div class="dropdown-menu-inner"> <div class="tb-megamenu-row row-fluid"> <div class="mega-submenu-header tb-megamenu-column span8 mega-col-nav" data-width="8"><a href="/people" data-mobile-explore-text="All People">People</a></div> </div> <div class="mega-dropdown-inner"> <div 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Jamie Lee Curtis, from right, and Ke Huy Quan are in the audience. Credit: Chris Pizzello/AP" class="image-style-news-listing" /> </a></div></div><div class="views-field views-field-title"><span class="field-content"><a href="/news/2024/help-ai-uc-berkeley-researchers-confirm-hollywood-getting-more-diverse" hreflang="en">With the Help of AI, UC Berkeley Researchers Confirm Hollywood Is Getting More Diverse</a></span></div><div class="views-field views-field-field-teaser-text"><div class="field-content">A new study led by Professor David Bamman used facial recognition technology to track the amount of time actors appear…</div></div></div> <div class="views-row"><div class="views-field views-field-field-media-image views-field-field-teaser-image"><div class="field-content"><a href="https://www.ischool.berkeley.edu/news/2024/dont-worry-study-shows-youre-likely-more-creative-writer-chatgpt-now"> <img loading="lazy" src="/sites/default/files/styles/news_listing/public/2024-10/adobestock_232311459-scaled.jpeg?h=0da08316&itok=oYSD3JPo" width="150" height="150" alt="robot hand using laptop" title="Photo Credit: sompong_tom via Adobe Images" class="image-style-news-listing" /> </a></div></div><div class="views-field views-field-title"><span class="field-content"><a href="/news/2024/dont-worry-study-shows-youre-likely-more-creative-writer-chatgpt-now" hreflang="en">Don’t Worry. Study Shows You’re Likely a More Creative Writer Than ChatGPT. For Now.</a></span></div><div class="views-field views-field-field-teaser-text"><div class="field-content">UC Berkeley researcher Nina Beguš instructed both humans and AI tools to write a story based on one of two short…</div></div></div> <div class="views-row"><div class="views-field views-field-field-media-image views-field-field-teaser-image"><div class="field-content"><a href="https://www.ischool.berkeley.edu/news/2024/white-house-issues-new-directive-ai-and-national-security"> <img loading="lazy" src="/sites/default/files/styles/news_listing/public/2024-10/tabrez-syed-dbc9dgsjzko-unsplash.jpg?h=8d5010cd&itok=Bzaog3H5" width="150" height="150" alt="photo of the White House at night" title="White House, Washington DC (Photo by Tabrez Syed via Unsplash)" class="image-style-news-listing" /> </a></div></div><div class="views-field views-field-title"><span class="field-content"><a href="/news/2024/white-house-issues-new-directive-ai-and-national-security" hreflang="en">White House Issues New Directive on AI and National Security</a></span></div><div class="views-field views-field-field-teaser-text"><div class="field-content">Professor Deirdre Mulligan explains the Biden-Harris Administration’s new National Security Memorandum (NSM) on…</div></div></div> <div class="views-row"><div class="views-field views-field-field-media-image views-field-field-teaser-image"><div class="field-content"><a href="https://www.ischool.berkeley.edu/news/2024/study-shows-election-data-visualization-design-can-be-powerful-persuasion-tool"> <img loading="lazy" src="/sites/default/files/styles/news_listing/public/article_teaser_image/chase.png?h=53247445&itok=h8zylsUq" width="150" height="150" alt="Headshot, chase, guy with glasses and blue shirt" title="Chase Stokes (Photo by Brittany Hosea-Small for the School of Information)" class="image-style-news-listing" /> </a></div></div><div class="views-field views-field-title"><span class="field-content"><a href="/news/2024/study-shows-election-data-visualization-design-can-be-powerful-persuasion-tool" hreflang="en">Study Shows Election Data Visualization Design Can Be a Powerful Persuasion Tool</a></span></div><div class="views-field views-field-field-teaser-text"><div class="field-content">From election forecasts and pandemic dashboards to stock market charts and scientific figures, many people trust data…</div></div></div> <div class="clearfix"></div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div></div> </li> <li class="tbm-item level-1 tbm-item--has-dropdown" aria-level="1" data-id="1184" > <div class="tbm-link-container"> <a href="/events" class="tbm-link level-1 tbm-toggle" aria-expanded="false"> Events </a> <button class="tbm-submenu-toggle"><span class="visually-hidden">Toggle submenu</span></button> </div> <div class="tbm-submenu tbm-item-child tbm-has-width" style="width: 1000px;" role="list"><div class="dropdown-menu-inner"> <div 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src="/sites/default/files/styles/news_listing/public/2024-11/ben-shestakofsky_0.jpg?h=6016224a&itok=lPEwjUQt" width="150" height="150" alt="Benjamin Shestakofsky" title="Benjamin Shestakofsky" class="image-style-news-listing" /> </a></div></div><div class="views-field views-field-title"><span class="field-content"><a href="/events/2024/behind-startup-how-venture-capital-shapes-work-innovation-and-inequality" hreflang="und">Behind the Startup: How Venture Capital Shapes Work, Innovation, and Inequality</a></span></div><div class="views-field views-field-field-event-date-time"><div class="field-content">December 5, 2024, 2:15 pm – 3:25 pm</div></div></div> <div class="views-row"><div class="views-field views-field-field-media-image views-field-field-teaser-image"><div class="field-content"><a href="https://www.ischool.berkeley.edu/events/2024/terms-disservice-stakes-human-chatbot-relationships"> <img loading="lazy" src="/sites/default/files/styles/news_listing/public/2024-11/valerie-black.png?h=f439324e&itok=Ug1kWsbw" width="150" height="150" alt="Valerie Black" title="Valerie Black" class="image-style-news-listing" /> </a></div></div><div class="views-field views-field-title"><span class="field-content"><a href="/events/2024/terms-disservice-stakes-human-chatbot-relationships" hreflang="und">Terms of (Dis)Service: The Stakes of Human-Chatbot Relationships</a></span></div><div class="views-field views-field-field-event-date-time"><div class="field-content">December 10, 2024, 2:15 pm – 3:25 pm</div></div></div> <div class="views-row"><div class="views-field views-field-field-media-image views-field-field-teaser-image"><div class="field-content"><a href="https://www.ischool.berkeley.edu/events/2024/cybersecurity-fall-2024-capstone-project-showcase"> <img loading="lazy" src="/sites/default/files/styles/news_listing/public/event_teaser_image/mics_banner_16x9.png?h=f30bcfc4&itok=fGVuUpMz" width="150" height="150" alt="mics_banner_16x9.png" class="image-style-news-listing" /> </a></div></div><div class="views-field views-field-title"><span class="field-content"><a href="/events/2024/cybersecurity-fall-2024-capstone-project-showcase" hreflang="und">Cybersecurity Fall 2024 Capstone Project Showcase</a></span></div><div class="views-field views-field-field-event-date-time"><div class="field-content">December 11, 2024, 4:00 pm – 6:30 pm</div></div></div> <div class="views-row"><div class="views-field views-field-field-media-image views-field-field-teaser-image"><div class="field-content"><a href="https://www.ischool.berkeley.edu/events/2024/uc-berkeley-cybersecurity-clinic-showcase"> <img loading="lazy" src="/sites/default/files/styles/news_listing/public/2024-11/citizenclinic.jpg?h=f0beca9a&itok=MLe4s0ve" width="150" height="150" alt="Graphic of multiple raised fists holding smartphones" class="image-style-news-listing" /> </a></div></div><div class="views-field views-field-title"><span class="field-content"><a href="/events/2024/uc-berkeley-cybersecurity-clinic-showcase" hreflang="en">UC Berkeley Cybersecurity Clinic Showcase</a></span></div><div class="views-field views-field-field-event-date-time"><div class="field-content">December 12, 2024, 12:30 pm – 2:00 pm</div></div></div> <div class="clearfix"></div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div></div> </li> </ul> </div> </div> </div> </div> </div> </header> <div class="l-main"> <div id="main-content" class="l-content" role="main"> <div class="layout-display clearfix"> <div class="l-region l-region--title"> <div id="block-pagetitle" class="block block-core block-page-title-block"> <div class="content"> </div> </div> </div> <div class="l-region l-region--content"> <div data-drupal-messages-fallback class="hidden"></div> <div id="block-i-school-i-school-system-main" class="block block-system block-system-main-block"> <div class="content"> <article class="node node--type-layout-page node--view-mode-default"> <div class="node__content"> <div class="i-school-layout two-column panel-2col-stacked"> <div class="main-region panel-col-first panel-panel"> <div class="views-element-container panel-pane block-views--course-catalog-block-2 block block-views block-views-blockcourse-catalog-block-2"> <div class="block-content"> <div><div class="view view-course-catalog view-id-course_catalog view-display-id-block_2 js-view-dom-id-af4addb8a903a97c38d99812d37580459bffef8f0891f626850fd8fea6bfc5c0"> <div class="view-content"> <div class="views-row"><div class="panel-pane pane-page-title"><h1>Catalog: Data Science Courses</h1></div></div> <div class="clearfix"></div> </div> </div> </div> </div> </div> <div class="pane-custom course-catalog-restriction block block-layout-builder block-inline-blockbasic"> <div class="content"> </div> </div> <div class="pane-custom course-catalog-restriction block block-layout-builder block-inline-blockbasic"> <div class="content"> <div class="clearfix text-formatted field field--name-body field--type-text-with-summary field--label-hidden field__item"><p>Data Science courses are restricted to students enrolled in the <a href="/programs/mids">MIDS degree program</a> only.</p></div> </div> </div> <div class="views-element-container panel-pane block-views--course-catalog-block-1 block block-views block-views-blockcourse-catalog-block-1"> <div class="block-content"> <div><div class="view view-course-catalog view-id-course_catalog view-display-id-block_1 js-view-dom-id-09d8ea3b3d73457eb168da21a0ecf39fbdc8fd937133089e817d37afa411bd7c"> <div class="view-content"> <h3>Graduate</h3> <div class="views-row"><div class="views-field views-field-nothing-1"><span class="field-content"><span id="7441" class="course-title"><a href="/courses/datasci/200" hreflang="und">Data Science 200. Introduction to Data Science Programming</a></span> (3 units)</span></div><div class="views-field views-field-nothing"><span class="field-content"><a href="#" class="collapse-trigger-cat"><span class="collapse-message collapse-sign">more information</span></a></span></div><div class="views-field views-field-field-course-catalog-description"><div class="field-content"><p>This fast-paced course gives students fundamental Python knowledge necessary for advanced work in data science. Students gain frequent practice writing code, building to advanced skills focused on data science applications. We introduce a range of Python objects and control structures, then build on these with classes on object-oriented programming. A major programming project reinforces these concepts, giving students insight into how a large piece of software is built and experience managing a full-cycle development project. The last section covers two popular Python packages for data analysis, NumPy and pandas, and includes an exploratory data analysis.</p></div></div></div> <div class="views-row"><div class="views-field views-field-nothing-1"><span class="field-content"><span id="351" class="course-title"><a href="/courses/datasci/201" hreflang="und">Data Science 201. Research Design and Applications for Data and Analysis</a></span> (3 units)</span></div><div class="views-field views-field-nothing"><span class="field-content"><a href="#" class="collapse-trigger-cat"><span class="collapse-message collapse-sign">more information</span></a></span></div><div class="views-field views-field-field-course-catalog-description"><div class="field-content"><p>Introduces the data sciences landscape, with a particular focus on learning data science techniques to uncover and answer the questions students will encounter in industry. Lectures, readings, discussions, and assignments will teach how to apply disciplined, creative methods to ask better questions, gather data, interpret results, and convey findings to various audiences. The emphasis throughout is on making practical contributions to real decisions that organizations will and should make.</p></div></div></div> <div class="views-row"><div class="views-field views-field-nothing-1"><span class="field-content"><span id="157" class="course-title"><a href="/courses/datasci/203" hreflang="und">Data Science 203. Statistics for Data Science</a></span> (3 units)</span></div><div class="views-field views-field-nothing"><span class="field-content"><a href="#" class="collapse-trigger-cat"><span class="collapse-message collapse-sign">more information</span></a></span></div><div class="views-field views-field-field-course-catalog-description"><div class="field-content"><p>An introduction to many different types of quantitative research methods and statistical techniques for analyzing data. We begin with a focus on measurement, inferential statistics and causal inference using the open-source statistics language, R. Topics in quantitative techniques include: descriptive and inferential statistics, sampling, experimental design, tests of difference, ordinary least squares regression, general linear models.</p></div></div></div> <div class="views-row"><div class="views-field views-field-nothing-1"><span class="field-content"><span id="299" class="course-title"><a href="/courses/datasci/205" hreflang="und">Data Science 205. Fundamentals of Data Engineering</a></span> (3 units)</span></div><div class="views-field views-field-nothing"><span class="field-content"><a href="#" class="collapse-trigger-cat"><span class="collapse-message collapse-sign">more information</span></a></span></div><div class="views-field views-field-field-course-catalog-description"><div class="field-content"><p>Storing, managing, and processing datasets are foundational processes in data science. This course introduces the fundamental knowledge and skills of data engineering that are required to be effective as a data scientist. This course focuses on the basics of data pipelines, data pipeline flows and associated business use cases, and how organizations derive value from data and data engineering. As these fundamentals of data engineering are introduced, learners will interact with data and data processes at various stages in the pipeline, understand key data engineering tools and platforms, and use and connect critical technologies through which one can construct storage and processing architectures that underpin data science applications.</p></div></div></div> <div class="views-row"><div class="views-field views-field-nothing-1"><span class="field-content"><span id="300" class="course-title"><a href="/courses/datasci/207" hreflang="und">Data Science 207. Applied Machine Learning</a></span> (3 units)</span></div><div class="views-field views-field-nothing"><span class="field-content"><a href="#" class="collapse-trigger-cat"><span class="collapse-message collapse-sign">more information</span></a></span></div><div class="views-field views-field-field-course-catalog-description"><div class="field-content"><p>Machine learning is a rapidly growing field at the intersection of computer science and statistics concerned with finding patterns in data. It is responsible for tremendous advances in technology, from personalized product recommendations to speech recognition in cell phones. This course provides a broad introduction to the key ideas in machine learning. The emphasis will be on intuition and practical examples rather than theoretical results, though some experience with probability, statistics, and linear algebra will be important.</p></div></div></div> <div class="views-row"><div class="views-field views-field-nothing-1"><span class="field-content"><span id="330" class="course-title"><a href="/courses/datasci/209" hreflang="und">Data Science 209. Data Visualization</a></span> (3 units)</span></div><div class="views-field views-field-nothing"><span class="field-content"><a href="#" class="collapse-trigger-cat"><span class="collapse-message collapse-sign">more information</span></a></span></div><div class="views-field views-field-field-course-catalog-description"><div class="field-content"><p>Visualization enhances exploratory analysis as well as efficient communication of data results. This course focuses on the design of visual representations of data in order to discover patterns, answer questions, convey findings, drive decisions, and provide persuasive evidence. The goal is to give you the practical knowledge you need to create effective tools for both exploring and explaining your data. Exercises throughout the course provide a hands-on experience using relevant programming libraries and software tools to apply research and design concepts learned.</p></div></div></div> <div class="views-row"><div class="views-field views-field-nothing-1"><span class="field-content"><span id="284" class="course-title"><a href="/courses/datasci/210" hreflang="und">Data Science 210. Capstone</a></span> (3 units)</span></div><div class="views-field views-field-nothing"><span class="field-content"><a href="#" class="collapse-trigger-cat"><span class="collapse-message collapse-sign">more information</span></a></span></div><div class="views-field views-field-field-course-catalog-description"><div class="field-content"><p>The capstone course will cement skills learned throughout the MIDS program — both core data science skills and “soft skills” like problem-solving, communication, influencing, and management — preparing students for success in the field. The centerpiece is a semester-long group project in which teams of students propose and select project ideas, conduct and communicate their work, receive and provide feedback (in informal group discussions and formal class presentations), and deliver compelling presentations along with a web-based final deliverable. Includes relevant readings, case discussions, and real-world examples and perspectives from panel discussions with leading data science experts and industry practitioners.</p></div></div></div> <div class="views-row"><div class="views-field views-field-nothing-1"><span class="field-content"><span id="18095" class="course-title"><a href="/courses/datasci/221" hreflang="und">Data Science 221. Modern Data Applications</a></span> (3 units)</span></div><div class="views-field views-field-nothing"><span class="field-content"><a href="#" class="collapse-trigger-cat"><span class="collapse-message collapse-sign">more information</span></a></span></div><div class="views-field views-field-field-course-catalog-description"><div class="field-content"><p>This is a multidisciplinary graduate course that synthesizes data management, data economy, and machine learning & AI strategy and research, product innovation, business and enterprise technology strategy, industry analysis, organizational decision-making and data-driven leadership into one course offering. The course provides strategic thinking tools, analytical frameworks, and real-world case examples to help students explore and investigate modern data applications and opportunities in multiple domains and industries. Students are required to participate in weekly sessions and write response pieces as well as a final paper and presentation evaluating one defining application or emerging technology in machine learning/AI end-to-end.</p></div></div></div> <div class="views-row"><div class="views-field views-field-nothing-1"><span class="field-content"><span id="329" class="course-title"><a href="/courses/datasci/231" hreflang="und">Data Science 231. Behind the Data: Humans and Values</a></span> (3 units)</span></div><div class="views-field views-field-nothing"><span class="field-content"><a href="#" class="collapse-trigger-cat"><span class="collapse-message collapse-sign">more information</span></a></span></div><div class="views-field views-field-field-course-catalog-description"><div class="field-content"><p>Intro to the legal, policy, and ethical implications of data, including privacy, surveillance, security, classification, discrimination, decisional-autonomy, and duties to warn or act. Examines legal, policy, and ethical issues throughout the full data-science life cycle collection, storage, processing, analysis, and use with case studies from criminal justice, national security, health, marketing, politics, education, employment, athletics, and development. Includes legal and policy constraints and considerations for specific domains and data-types, collection methods, and institutions; technical, legal, and market approaches to mitigating and managing concerns; and the strengths and benefits of competing and complementary approaches.</p></div></div></div> <div class="views-row"><div class="views-field views-field-nothing-1"><span class="field-content"><span id="13426" class="course-title"><a href="/courses/datasci/233" hreflang="und">Data Science 233. Privacy Engineering</a></span> (3 units)</span></div><div class="views-field views-field-nothing"><span class="field-content"><a href="#" class="collapse-trigger-cat"><span class="collapse-message collapse-sign">more information</span></a></span></div><div class="views-field views-field-field-course-catalog-description"><div class="field-content"><p>This course surveys privacy mechanisms applicable to systems engineering, with a particular focus on the inference threat arising due to advancements in artificial intelligence and machine learning. We will briefly discuss the history of privacy and compare two major examples of general legal frameworks for privacy from the United States and the European Union. We then survey three design frameworks of privacy that may be used to guide the design of privacy-aware information systems. Finally, we survey threat-specific technical privacy frameworks and discuss their applicability in different settings, including statistical privacy with randomized responses, anonymization techniques, semantic privacy models, and technical privacy mechanisms.</p></div></div></div> <div class="views-row"><div class="views-field views-field-nothing-1"><span class="field-content"><span id="297" class="course-title"><a href="/courses/datasci/241" hreflang="und">Data Science 241. Experiments and Causal Inference</a></span> (3 units)</span></div><div class="views-field views-field-nothing"><span class="field-content"><a href="#" class="collapse-trigger-cat"><span class="collapse-message collapse-sign">more information</span></a></span></div><div class="views-field views-field-field-course-catalog-description"><div class="field-content"><p>This course introduces students to experimentation in the social sciences. This topic has increased considerably in importance since 1995, as researchers have learned to think creatively about how to generate data in more scientific ways, and developments in information technology have facilitated the development of better data gathering. Key to this area of inquiry is the insight that correlation does not necessarily imply causality. In this course, we learn how to use experiments to establish causal effects and how to be appropriately skeptical of findings from observational data.</p></div></div></div> <div class="views-row"><div class="views-field views-field-nothing-1"><span class="field-content"><span id="14975" class="course-title"><a href="/courses/datasci/255" hreflang="und">Data Science 255. Machine Learning Systems Engineering</a></span> (3 units)</span></div><div class="views-field views-field-nothing"><span class="field-content"><a href="#" class="collapse-trigger-cat"><span class="collapse-message collapse-sign">more information</span></a></span></div><div class="views-field views-field-field-course-catalog-description"><div class="field-content"><p>This course provides learners hands-on data management and systems engineering experience using containers, cloud, and Kubernetes ecosystems based on current industry practice. The course will be project-based with an emphasis on how production systems are used at leading technology-focused companies and organizations. During the course, learners will build a body of knowledge around data management, architectural design, developing batch and streaming data pipelines, scheduling, and security around data including access management and auditability. We’ll also cover how these tools are changing the technology landscape.</p></div></div></div> <div class="views-row"><div class="views-field views-field-nothing-1"><span class="field-content"><span id="289" class="course-title"><a href="/courses/datasci/261" hreflang="und">Data Science 261. Machine Learning at Scale</a></span> (3 units)</span></div><div class="views-field views-field-nothing"><span class="field-content"><a href="#" class="collapse-trigger-cat"><span class="collapse-message collapse-sign">more information</span></a></span></div><div class="views-field views-field-field-course-catalog-description"><div class="field-content"><p>This course teaches the underlying principles required to develop scalable machine learning pipelines for structured and unstructured data at the petabyte scale. Students will gain hands-on experience in Apache Hadoop and Apache Spark.</p></div></div></div> <div class="views-row"><div class="views-field views-field-nothing-1"><span class="field-content"><span id="352" class="course-title"><a href="/courses/datasci/266" hreflang="und">Data Science 266. Natural Language Processing with Deep Learning</a></span> (3 units)</span></div><div class="views-field views-field-nothing"><span class="field-content"><a href="#" class="collapse-trigger-cat"><span class="collapse-message collapse-sign">more information</span></a></span></div><div class="views-field views-field-field-course-catalog-description"><div class="field-content"><p>Understanding language is fundamental to human interaction. Our brains have evolved language-specific circuitry that helps us learn it very quickly; however, this also means that we have great difficulty explaining how exactly meaning arises from sounds and symbols. This course is a broad introduction to linguistic phenomena and our attempts to analyze them with machine learning. We will cover a wide range of concepts with a focus on practical applications such as information extraction, machine translation, sentiment analysis, and summarization.</p></div></div></div> <div class="views-row"><div class="views-field views-field-nothing-1"><span class="field-content"><span id="18882" class="course-title"><a href="/courses/datasci/267" hreflang="und">Data Science 267. Generative AI</a></span> (3 units)</span></div><div class="views-field views-field-nothing"><span class="field-content"><a href="#" class="collapse-trigger-cat"><span class="collapse-message collapse-sign">more information</span></a></span></div><div class="views-field views-field-field-course-catalog-description"><div class="field-content"><p>This course focuses on the practical aspects of LLMs to enable students to be effective and responsible users of generative AI technologies. The course has three parts. Introduction section covers the historical aspects, key technical ideas and learnings all the way to transformer architectures and various LLM training aspects. The Practical Aspects and Techniques section, students learn how to train, deploy, and use LLMs; and discuss core concepts like prompt tuning, quantization, and parameter efficient fine-tuning, and explore use case patterns. Finally, a discussion of challenges & opportunities offered by generative AI, which includes highlighting critical issues like bias and inclusivity, fake information, safety, and some IP issues.</p></div></div></div> <div class="views-row"><div class="views-field views-field-nothing-1"><span class="field-content"><span id="293" class="course-title"><a href="/courses/datasci/271" hreflang="und">Data Science 271. Statistical Methods for Discrete Response, Time Series, and Panel Data</a></span> (3 units)</span></div><div class="views-field views-field-nothing"><span class="field-content"><a href="#" class="collapse-trigger-cat"><span class="collapse-message collapse-sign">more information</span></a></span></div><div class="views-field views-field-field-course-catalog-description"><div class="field-content"><p>A continuation of Data Science 203 (Statistics for Data Science), this course trains data science students to apply more advanced methods from regression analysis and time series models. Central topics include linear regression, causal inference, identification strategies, and a wide-range of time series models that are frequently used by industry professionals. Throughout the course, we emphasize choosing, applying, and implementing statistical techniques to capture key patterns and generate insight from data. Students who successfully complete this course will be able to distinguish between appropriate and inappropriate techniques given the problem under consideration, the data available, and the given timeframe.</p></div></div></div> <div class="views-row"><div class="views-field views-field-nothing-1"><span class="field-content"><span id="14976" class="course-title"><a href="/courses/datasci/281" hreflang="und">Data Science 281. Computer Vision</a></span> (3 units)</span></div><div class="views-field views-field-nothing"><span class="field-content"><a href="#" class="collapse-trigger-cat"><span class="collapse-message collapse-sign">more information</span></a></span></div><div class="views-field views-field-field-course-catalog-description"><div class="field-content"><p>This course introduces the theoretical and practical aspects of computer vision, covering both classical and state of the art deep-learning based approaches. This course covers everything from the basics of the image formation process in digital cameras and biological systems, through a mathematical and practical treatment of basic image processing, space/frequency representations, classical computer vision techniques for making 3-D measurements from images, and modern deep-learning based techniques for image classification and recognition.</p></div></div></div> <div class="views-row"><div class="views-field views-field-nothing-1"><span class="field-content"><span id="14590" class="course-title"><a href="/courses/datasci/290" hreflang="und">Data Science 290. Special Topics</a></span> (3 units)</span></div><div class="views-field views-field-nothing"><span class="field-content"><a href="#" class="collapse-trigger-cat"><span class="collapse-message collapse-sign">more information</span></a></span></div><div class="views-field views-field-field-course-catalog-description"><div class="field-content"><p>Specific topics, may vary from section to section, year to year. Course may be repeated for credit when topic changes. 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