Programming Methodology
The most beloved intro CS course ever recorded.

Stanford University · official site
The home of CS106A and the birthplace of modern machine learning teaching. Stanford publishes its most famous engineering courses on the open web.
Free, complete, and yours to keep — stream every lecture in our player or download the whole course.
The most beloved intro CS course ever recorded.
Word vectors to transformers — the definitive NLP course.
The course that launched a thousand careers — taught by Andrew Ng himself.
A seminar where the people who built transformers explain them.
The canonical graduate text on convex optimization — from Stanford's Boyd & Vandenberghe, free to download.
Jurafsky & Martin's definitive NLP textbook, rewritten for the era of large language models — free in draft from Stanford.
The optimization course that industry keeps quietly stealing.
Stanford's survey of AI — search, games, MDPs, and machine learning under one roof.
The science of networks — from PageRank to graph neural networks.
The mathematics of signal and image — a Stanford classic.
C++, recursion, and data structures — the classic follow-up to CS106A.
Stephen Boyd's own course — state-space systems, reachability, and least squares at work.
Build a large language model end to end — Stanford's course on how the machine is actually made.
Why is my program not faster? — the parallel computing course for the many-core era.
C, assembly, and the machine beneath your language.
How machines learn to learn — Chelsea Finn's graduate course on meta-learning.
Agents that learn from consequences — taught with unusual rigor.
When algorithms meet strategic humans — auctions, pricing, and the internet.
The course that taught the world to teach machines to see.
Andrew Ng's applied deep learning course, freshly updated.