Stanford courses in Computer Science with Artificial Intelligence: [CS-BS Program | Stanford University Bulletin](https://bulletin.stanford.edu/programs/CS-BS) [CS-MS Program | Stanford University Bulletin](https://bulletin.stanford.edu/programs/CS-MS) [CS-PHD Program | Stanford University Bulletin](https://bulletin.stanford.edu/programs/CS-PHD) CS272 - Introduction to Biomedical Data Science Research Methodology CS341 - Project in Mining Massive Data Sets CS231A - Computer Vision: From 3D Perception to 3D Reconstruction and Beyond PHYSICS81 - Electricity and Magnetism Using Special Relativity and Vector Calculus MATH53 - Differential Equations with Linear Algebra, Fourier Methods, and Modern Applications CS245 - Principles of Data-Intensive Systems CS398 - Computational Education CS247S - Service Design CS232 - Digital Image Processing CS197C - Computer Science Research: CURIS Internship Onramp CS377T - Topics in Human-Computer Interaction: Teaching Studio Classes CS336 - Robot Perception and Decision-Making: Optimal and Learning-based Approaches CS253 - Web Security CS111 - Operating Systems Principles CS143 - Compilers CS223A - Introduction to Robotics CS269I - Incentives in Computer Science STATS203 - Introduction to Regression Models and Analysis of Variance CS229B - Machine Learning for Sequence Modeling CS224C - NLP for Computational Social Science CS329T - Trustworthy Machine Learning CS217 - Hardware Accelerators for Machine Learning CS348A - Computer Graphics: Geometric Modeling & Processing ENGR209A - Analysis and Control of Nonlinear Systems STATS116 - Theory of Probability CS377E - Designing Solutions to Global Grand Challenges CS163 - The Practice of Theory Research CS259Q - Quantum Computing CS224N - Natural Language Processing with Deep Learning CS206 - Exploring Computational Journalism CS227B - General Game Playing CS275 - Translational Bioinformatics CS279 - Computational Biology: Structure and Organization of Biomolecules and Cells CS237A - Principles of Robot Autonomy I CS428 - Computation and Cognition: The Probabilistic Approach CS149 - Parallel Computing CS325B - Data for Sustainable Development CS329E - Machine Learning on Embedded Systems CS375 - Large-Scale Neural Network Modeling for Neuroscience CS145 - Data Management and Data Systems EE278 - Probability and Statistical Inference CS333 - Algorithms for Interactive Robotics PHIL152 - Computability and Logic EE276 - Information Theory CS269O - Introduction to Optimization Theory CS140 - Operating Systems and Systems Programming EE267 - Virtual Reality ENGR205 - Introduction to Control Design Techniques CME106 - Introduction to Probability and Statistics for Engineers CS377Q - Designing for Accessibility MS&E355 - Influence Diagrams and Probabilistics Networks STATS202 - Data Mining and Analysis CS254 - Computational Complexity CS112 - Operating systems kernel implementation project MATH104 - Applied Matrix Theory EE180 - Digital Systems Architecture CS210B - Software Project Experience with Corporate Partners CS329H - Machine Learning from Human Preferences CS123 - A Hands-On Introduction to Building AI-Enabled Robots CS247B - Design for Behavior Change CS249I - The Modern Internet PHIL151 - Metalogic CME108 - Introduction to Scientific Computing MS&E251 - Introduction to Stochastic Control with Applications CS240 - Advanced Topics in Operating Systems PSYCH204A - Human Neuroimaging Methods CS276 - Information Retrieval and Web Search EE178 - Probabilistic Systems Analysis CS242 - Programming Languages CS107 - Computer Organization and Systems CS255 - Introduction to Cryptography CS329R - Race and Natural Language Processing CS428A - Probabilistic models of cognition: Reasoning and Learning [CS-BS Program | Stanford University Bulletin](https://bulletin.stanford.edu/programs/CS-BS) CS377J - Designing Systems for Collaboration, Cooperation, and Collective Action CS348K - Visual Computing Systems CS293 - Empowering Educators via Language Technology CS399 - Independent Project CS108 - Object-Oriented Systems Design CS281 - Ethics of Artificial Intelligence CS103 - Mathematical Foundations of Computing CS332 - Advanced Survey of Reinforcement Learning CS257 - Introduction to Automated Reasoning CS237B - Principles of Robot Autonomy II CS144 - Introduction to Computer Networking MATH20 - Calculus CS377U - Understanding Users STATS200 - Introduction to Statistical Inference CS246 - Mining Massive Data Sets MATH109 - Groups and Symmetry CS348E - Character Animation: Modeling, Simulation, and Control of Human Motion CS231C - Computer Vision and Image Analysis of Art CS205L - Continuous Mathematical Methods with an Emphasis on Machine Learning CS151 - Logic Programming CS224U - Natural Language Understanding CS190 - Software Design Studio CS244 - Advanced Topics in Networking CS348C - Computer Graphics: Animation and Simulation CS261 - Optimization and Algorithmic Paradigms CS109 - Introduction to Probability for Computer Scientists STATS271 - Applied Bayesian Statistics CS148 - Introduction to Computer Graphics and Imaging CS235 - Computational Methods for Biomedical Image Analysis and Interpretation CS247L - Human Computer Interaction Technology Laboratory STATS205 - Introduction to Nonparametric Statistics EE364A - Convex Optimization I CS173A - Foundations of Computational Human Genomics CS147L - Cross-platform Mobile App Development CS239 - Advanced Topics in Sequential Decision Making CS428B - Probabilistic Models of Cognition: Language CS327A - Advanced Robotic Manipulation CS351 - Open Problems in Coding Theory MATH108 - Introduction to Combinatorics and Its Applications OR PHYSICS21 - Mechanics and Fluids CS336 - Language Modeling from Scratch CS379C - Computational Models of the Neocortex CS154 - Introduction to the Theory of Computation CS142 - Web Applications CS177 - Human Centered Product Management EE374 - Blockchain Foundations CS155 - Computer and Network Security CS236 - Deep Generative Models CS254B - Computational Complexity II CS329D - Machine Learning Under Distributional Shifts CS329M - Machine Programming CS342 - Building for Digital Health CS195 - Supervised Undergraduate Research CS251 - Cryptocurrencies and blockchain technologies CS329X - Human Centered NLP CS377I - Designing for Complexity PSYCH204B - Computational Neuroimaging: Data Analyses and Experimental Designs MS&E252 - Foundations of Decision Analysis CS221 - Artificial Intelligence: Principles and Techniques CS247A - Design for Artificial Intelligence MS&E220 - Probabilistic Analysis CS329 - Topics in Artificial Intelligence CS373 - Statistical and Machine Learning Methods for Genomics CS270 - Modeling Biomedical Systems CS244B - Distributed Systems MATH19 - Calculus CS250 - Algebraic Error Correcting Codes MS&E351 - Dynamic Programming and Stochastic Control CS106B - Programming Abstractions PHYSICS23 - Electricity, Magnetism, and Optics CS225A - Experimental Robotics CS212 - Operating Systems and Systems Programming CS338 - Physical Human Robot Interaction MATH113 - Linear Algebra and Matrix Theory CS224R - Deep Reinforcement Learning MS&E226 - Fundamentals of Data Science: Prediction, Inference, Causality CS247I - Design for Understanding EE377 - Information Theory and Statistics PSYCH209 - Neural Network Models of Cognition CS197 - Computer Science Research CS228 - Probabilistic Graphical Models: Principles and Techniques CS240LX - Advanced Systems Laboratory, Accelerated CS229S - Systems for Machine Learning CS161 - Design and Analysis of Algorithms CS329P - Practical Machine Learning MATH21 - Calculus EE282 - Computer Systems Architecture CME102 - Ordinary Differential Equations for Engineers CS252 - Analysis of Boolean Functions CS265 - Randomized Algorithms and Probabilistic Analysis CS229 - Machine Learning CS230 - Deep Learning CS243 - Program Analysis and Optimizations CS273C - Cloud Computing for Biology and Healthcare MATH52 - Integral Calculus of Several Variables CS361 - Engineering Design Optimization CS377 - Topics in Human-Computer Interaction ENGR40M - An Intro to Making: What is EE CS324H - History of Natural Language Processing CS271 - Artificial Intelligence in Healthcare ENGR108 - Introduction to Matrix Methods CS229T - Machine Learning Theory: A Modern Perspective CS224V - Conversational Virtual Assistants with Deep Learning CS278 - Social Computing CS348B - Computer Graphics: Image Synthesis Techniques CS353 - Seminar on Logic & Formal Philosophy CS448 - Topics in Computer Graphics EE364B - Convex Optimization II EE263 - Introduction to Linear Dynamical Systems CS140E - Operating systems design and implementation CS274 - Representations and Algorithms for Computational Molecular Biology CS373 - Statistical and Machine Learning Methods for GenomicsCS273B - Deep Learning in Genomics and Biomedicine CS166 - Data Structures MS&E352 - Decision Analysis II: Professional Decision Analysis CS107E - Computer Systems from the Ground Up CS329S - Machine Learning Systems Design CS247 - Human-Computer Interaction Design Studio CS269Q - Elements of Quantum Computer Programming MATH51 - Linear Algebra, Multivariable Calculus, and Modern Applications CS233 - Geometric and Topological Data Analysis CS368 - Algorithmic Techniques for Big Data CS377G - Designing Serious Games CS157 - Computational Logic CME100 - Vector Calculus for Engineers PHYSICS43 - Electricity and Magnetism CS234 - Reinforcement Learning CS256 - Algorithmic Fairness CS326 - Topics in Advanced Robotic Manipulation CS263 - Counting and Sampling CS322 - Triangulating Intelligence: Melding Neuroscience, Psychology, and AI STATS315A - Modern Applied Statistics: Learning CS248B - Fundamentals of Computer Graphics: Animation and Simulation CS348I - Computer Graphics in the Era of AI CS168 - The Modern Algorithmic Toolbox CS432 - Computer Vision for Education and Social Science Research CS371 - Computational Biology in Four Dimensions CS224S - Spoken Language Processing OR PHYSICS61 - Mechanics and Special Relativity CS229M - Machine Learning Theory CS224W - Machine Learning with Graphs CS328 - Foundations of Causal Machine Learning CS377N - Introduction to the Design of Smart Products MATH107 - Graph Theory CS124 - From Languages to Information CS324 - Advances in Foundation Models CS248A - Computer Graphics: Rendering, Geometry, and Image Manipulation MATH110 - Number Theory for Cryptography CS231N - Deep Learning for Computer Vision CS147 - Introduction to Human-Computer Interaction Design PHYSICS41 - Mechanics CME104 - Linear Algebra and Partial Differential Equations for Engineers CS247G - Design for Play CS330 - Deep Multi-task and Meta Learning CS348N - Neural Models for 3D Geometry CS225 - Machine Learning for Discrete Optimization ENGR76 - Information Science and Engineering CS210A - Software Project Experience with Corporate Partners STATS315B - Modern Applied Statistics: Learning II CS131 - Computer Vision: Foundations and Applications MS&E234 - Data Privacy and Ethics CS238 - Decision Making under Uncertainty Stanford, MIT, Berkeley, Princeton etc. courses in Computer Science with Artificial Intelligence, Information, Theoretical computer science, Physics, Mathematics, Engineering, Formal sciences, Natural sciences