stanford-cs221/lectures: Executable lectures for Autumn 2025

CS221 Autumn 2026 Lectures

Welcome to CS221! This repository contains all the (executable) lectures, which are made using edtrace.

Each lecture consists of stepping through Python files which you can either view in your browser on the links below or run locally if you clone this repository. If you notice any problems or have any questions, please file an GitHub issue or submit a pull request.

To run locally:

apt-get install graphviz uv sync rc python -m edtrace.execute -m welcome

git clone [email protected]:percyliang/edtrace (cd edtrace/frontend && npm i) npm --prefix edtrace/frontend run dev -- --port 2210

Lecture 1 (Tue Sep 22): Overview

• welcome
• history
• tensors

Lecture 2 (Thu Sep 24): Learning I

• backpropagation
• linear_regression

Lecture 3 (Tue Sep 29): Learning II

• linear_classification

Lecture 4 (Thu Oct 1): Learning III

• deep_learning

Lecture 5 (Tue Oct 6): Search I

• search

Lecture 6 (Thu Oct 8): Search II

• ucs_astar

Lecture 7 (Tue Oct 13): RL I

• mdp

Lecture 8 (Thu Oct 15): RL II

• reinforcement_learning

Lecture 9 (Tue Oct 20): RL III

• function_approximation
• policy_gradient

Lecture 10 (Thu Oct 22): RL IV

• improved_policy_gradient

Lecture 11 (Tue Oct 27): Games I

• games

Lecture 12 (Thu Oct 29): Games II

• td_learning
• simultaneous_games

Lecture 13 (Thu Nov 5): Bayesian Networks I

• bayes

Lecture 14 (Tue Nov 10): Bayesian Networks II

• gibbs_sampling

Lecture 15 (Thu Nov 12): Bayesian Networks III

• bayes_learning

Lecture 16 (Tue Nov 17): Logic I

• propositional_logic

Lecture 17 (Thu Nov 19): Logic II

• first_order_logic

Lecture 18 (Tue Dec 1): AI & Society

• society

Lecture 19 (Thu Dec 3): Fireside Chat, Conclusion