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