{"id":889,"date":"2026-11-02T13:41:10","date_gmt":"2026-11-02T18:41:10","guid":{"rendered":"https:\/\/web.uri.edu\/iacr\/?page_id=889"},"modified":"2026-11-04T14:07:37","modified_gmt":"2026-11-04T19:07:37","slug":"applied-ai-courses","status":"publish","type":"page","link":"https:\/\/web.uri.edu\/iacr\/applied-ai-courses\/","title":{"rendered":"Applied AI Courses"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">In Spring 2027 URI offers courses that teach artificial intelligence through its use in the sciences rather than as a computer-science subject. They are aimed at different students and go to different depths, so they complement each other. The courses are listed by level. Questions about whether a course is right for you are best sent to the instructor directly.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Undergraduate courses<\/h2>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><thead><tr><th><\/th><th>OCG 494<br>AI in Marine &amp; Earth Sciences<\/th><th>CMB 427X<br>Life Sciences Applications of AI<\/th><th>AMS 490<br>Applied Mathematics for ML and AI<\/th><\/tr><\/thead><tbody><tr><th>Register for<\/th><td>OCG 494-0012 on e-Campus (listed as \u201cSpecial Problems And Independent Study In Oceanography\u201d)<\/td><td>CMB 427X-0001<\/td><td>AMS 490-0001 (listed as \u201cIntermediate Topics in Applied Mathematics\u201d)<\/td><\/tr><tr><th>Level<\/th><td>Juniors and seniors<\/td><td>Juniors and seniors; also open to graduate students<\/td><td>Undergraduate<\/td><\/tr><tr><th>Credits and grading<\/th><td>3 credits, pass\/fail<\/td><td>3 credits, letter grade<\/td><td>4 credits, letter grade<\/td><\/tr><tr><th>Meets<\/th><td>Mon &amp; Wed 3:00\u20134:15 pm, Bliss Hall 210<\/td><td>Time and room to be announced<\/td><td>Mon &amp; Wed 2:00\u20133:50 pm, Chafee Hall 208<\/td><\/tr><tr><th>Dates<\/th><td>Jan 26 \u2013 May 3, 2027<\/td><td>Jan 26 \u2013 May 3, 2027<\/td><td>Jan 26 \u2013 May 3, 2027<\/td><\/tr><tr><th>Enrollment cap<\/th><td>20\u201325<\/td><td>20<\/td><td>35<\/td><\/tr><tr><th>Approach<\/th><td>Use AI tools on real data and judge their results critically<\/td><td>Apply existing AI models to biological data, build simple neural networks, and evaluate how well they work<\/td><td>Learn the mathematics behind machine learning and implement it yourself in Python<\/td><\/tr><tr><th>Topics<\/th><td>Landmark AI applications in the field; species distribution and habitat mapping; clustering, remote sensing and time series; model trust and validation<\/td><td>AI applications in genomics, structural biology and imaging; sequence, structure and image data; CNNs, autoencoders, graph networks, RNNs and transformers; AlphaFold 3 and Segment Anything<\/td><td>Multivariable calculus and the chain rule; linear algebra, eigenvalues and SVD; optimization and gradient descent; tensors and automatic differentiation; activation and loss functions<\/td><\/tr><tr><th>Coding<\/th><td>None required; notebooks and AI coding agents provided<\/td><td>None required; Python and PyTorch introduced in class, all work in Google Colab<\/td><td>Working Python required; Jupyter notebooks, with PyTorch taught in the weekly labs<\/td><\/tr><tr><th>Project<\/th><td>Individual or pair, data-analysis or critical-assessment track<\/td><td>Two projects, individual or teams of up to 3: each applies AI models to biological data in a report with a literature review<\/td><td>Small group: model and solve a real-world problem, with proposal, report and presentation in place of a final exam<\/td><\/tr><tr><th>Instructor<\/th><td>Meng (Matt) Wei, Oceanography<\/td><td>Pengyu (Peter) Liu, Mathematics and Applied Mathematical Sciences, Cell and Molecular Biology<\/td><td>Pengyu (Peter) Liu, Mathematics and Applied Mathematical Sciences, Cell and Molecular Biology<\/td><\/tr><tr><th>Email<\/th><td><a href=\"mailto:matt-wei@uri.edu\">matt-wei@uri.edu<\/a><\/td><td><a href=\"mailto:pengyu.liu@uri.edu\">pengyu.liu@uri.edu<\/a><\/td><td><a href=\"mailto:pengyu.liu@uri.edu\">pengyu.liu@uri.edu<\/a><\/td><\/tr><tr><th>Syllabus<\/th><td><a href=\"https:\/\/web.uri.edu\/iacr\/wp-content\/uploads\/sites\/2282\/AI_MES_S27.pdf\">Syllabus (PDF)<\/a><\/td><td><a href=\"https:\/\/web.uri.edu\/iacr\/wp-content\/uploads\/sites\/2282\/CMB427X_Syllabus.pdf\">Syllabus (PDF)<\/a><\/td><td><a href=\"https:\/\/web.uri.edu\/iacr\/wp-content\/uploads\/sites\/2282\/AMS490_Syllabus.pdf\">Syllabus (PDF)<\/a> \u00b7\u00a0<a href=\"https:\/\/sail-uri.github.io\/posters\/ams490.html\">Flyer<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Which one is for me?<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Marine biology, geosciences, environmental sciences, natural resources, fisheries, aquaculture or marine affairs, and no coding background:\u00a0<strong>OCG 494<\/strong>.<\/li>\n\n\n\n<li>Life sciences, with an interest in genomics, protein structure or biological imaging, and no programming experience:\u00a0<strong>CMB 427X<\/strong>.<\/li>\n\n\n\n<li>Calculus, linear algebra and some Python, and you want the mathematics that makes machine learning work:\u00a0<strong>AMS 490<\/strong>.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Graduate courses<\/h2>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><thead><tr><th><\/th><th>OCG 593<br>AI Tools for Graduate Research in the Ocean, Environmental and Life Sciences<\/th><th>PHY 591<br>AAI4STEM: Applications of AI Methods Across STEM Disciplines<\/th><\/tr><\/thead><tbody><tr><th>Register for<\/th><td>OCG 593 (listed as \u201cSpecial Studies\u201d)<\/td><td>PHY 591-0001 (listed as \u201cSpecial Problems\u201d)<\/td><\/tr><tr><th>Level<\/th><td>Graduate (MS and PhD, thesis or non-thesis)<\/td><td>Graduate (MS and PhD); advanced undergraduates by permission<\/td><\/tr><tr><th>Credits and grading<\/th><td>3 credits, letter grade<\/td><td>3 credits, letter grade<\/td><\/tr><tr><th>Meets<\/th><td>Mon &amp; Wed 9:00\u201310:15 am, Watkins Hall 12, Narragansett Bay Campus<\/td><td>Tue &amp; Thu 11:00 am\u201312:15 pm, Swan Hall 211<\/td><\/tr><tr><th>Dates<\/th><td>Jan 26 \u2013 May 3, 2027<\/td><td>Jan 26 \u2013 May 3, 2027<\/td><\/tr><tr><th>Enrollment cap<\/th><td>\u2014<\/td><td>20<\/td><\/tr><tr><th>Approach<\/th><td>Use off-the-shelf AI tools on your own research data, verify everything they produce, and decide when they help<\/td><td>Build AI methods from scratch and test them against classical methods<\/td><\/tr><tr><th>Topics<\/th><td>What language models can and cannot do; AI policy and disclosure; reproducible project folders with Claude Code and git; data cleaning, analysis and figures; literature and science communication; public-data pipelines and lab tools; data privacy and environmental justice<\/td><td>Probability and deep-learning foundations; graph networks, physics-informed networks, neural ODEs, CNNs and transformers, normalizing flows, diffusion models, reinforcement learning<\/td><\/tr><tr><th>Coding<\/th><td>None required; students work in Claude Code<\/td><td>Working Python required; PyTorch taught in the course<\/td><\/tr><tr><th>Project<\/th><td>Individual, on your own research data or a course dataset: a project folder, verification log and AI-use statement for your thesis<\/td><td>Team of 2\u20133: a mini-project that grows into a capstone<\/td><\/tr><tr><th>Instructor<\/th><td>Kris Lewis, Oceanography<\/td><td>Michael P\u00fcrrer, Physics<\/td><\/tr><tr><th>Email<\/th><td><a href=\"mailto:kristy.lewis@uri.edu\">kristy.lewis@uri.edu<\/a><\/td><td><a href=\"mailto:mpuerrer@uri.edu\">mpuerrer@uri.edu<\/a><\/td><\/tr><tr><th>Syllabus<\/th><td><a href=\"https:\/\/web.uri.edu\/iacr\/wp-content\/uploads\/sites\/2282\/flyer-Lewis-AI-Ocean-ES-Life.pdf\">Flyer (PDF)<\/a><\/td><td><a href=\"https:\/\/web.uri.edu\/iacr\/wp-content\/uploads\/sites\/2282\/PHY591-Syllabus-Spring2027.pdf\">Syllabus (PDF)<\/a>, <a href=\"https:\/\/web.uri.edu\/iacr\/wp-content\/uploads\/sites\/2282\/PHY591-Flyer-Spring2027.jpg\" rel=\"lightbox[889]\">flyer<\/a><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Which one is for me?<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Ocean, environmental or life sciences, and you want to use AI tools on your own thesis or project data while checking everything they give you, with no programming needed:\u00a0<strong>OCG 593<\/strong>.<\/li>\n\n\n\n<li>Any STEM field, with linear algebra, calculus, probability and some Python, and you want to understand and build the methods behind modern scientific AI:\u00a0<strong>PHY 591<\/strong>. Advanced undergraduates with that background can join by permission.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">OCG 593 and PHY 591 meet at different times and can be taken together. Graduate students in the life sciences can also take CMB 427X, listed with the undergraduate courses.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\" \/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Teaching an AI course at URI?<\/strong>&nbsp;To have it listed on this page, write to&nbsp;<a href=\"mailto:mpuerrer@uri.edu\">mpuerrer@uri.edu<\/a>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><em>Last updated November 2026.<\/em><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In Spring 2027 URI offers courses that teach artificial intelligence through its use in the sciences rather than as a computer-science subject. They are aimed at different students and go to different depths, so they complement each other. The courses are listed by level. Questions about whether a course is right for you are best [&hellip;]<\/p>\n","protected":false},"author":4727,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"class_list":["post-889","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/web.uri.edu\/iacr\/wp-json\/wp\/v2\/pages\/889","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/web.uri.edu\/iacr\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/web.uri.edu\/iacr\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/iacr\/wp-json\/wp\/v2\/users\/4727"}],"replies":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/iacr\/wp-json\/wp\/v2\/comments?post=889"}],"version-history":[{"count":5,"href":"https:\/\/web.uri.edu\/iacr\/wp-json\/wp\/v2\/pages\/889\/revisions"}],"predecessor-version":[{"id":915,"href":"https:\/\/web.uri.edu\/iacr\/wp-json\/wp\/v2\/pages\/889\/revisions\/915"}],"wp:attachment":[{"href":"https:\/\/web.uri.edu\/iacr\/wp-json\/wp\/v2\/media?parent=889"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}