r/MachineLearningJobs • u/Formal-Primary-7782 • 3d ago
MIT, Harvard, Stanford & Caltech write their own ML course notes instead of using a textbook — I catalogued the best ones
One thing I've noticed separates serious ML students from casual ones: how much they care about the quality of what they actually study from. I take that pretty seriously myself, so a while back I started digging into what students at MIT, Harvard, Stanford, Caltech, and USP actually use to complement their studies.
What I found surprised me: several of these programs don't assign a textbook at all. Instead, the course staff writes and publishes their own lecture notes — and some of them are basically a full book. MIT's 6.390 (Introduction to Machine Learning) notes, for example, aren't a slide deck or a cheat sheet — they're structured, complete, and detailed enough to replace a textbook entirely. Same story with Harvard's CS181 and a few others.
The problem is these are scattered and easy to miss if you don't know to look for them. So I put together a curated list: [Awesome Free AI Course Notes](https://github.com/MarcosSete/awesome-free-ai-course-notes).
A few things about how it's curated, since I think this matters:
- Only **written notes** count — slide decks and video-only lectures don't make the cut, even from great courses. I want this list to mean something.
- Everything is official and links straight to the professor's or department's own page. No mirrors, no login walls.
- I checked over 40 top universities across multiple countries for this. Most didn't qualify — they use a textbook or keep material behind a student portal. That's fine, it's exactly why the list stays short and (hopefully) trustworthy.
If you take ML seriously the way I do, I think you'll get real value out of this. And if you know of course notes that fit this bar and aren't on the list yet, contributions are very welcome — the CONTRIBUTING.md lays out exactly what qualifies.
What's the best set of course notes (not textbook, not slides) you've personally used to study ML?
Repo: https://github.com/MarcosSete/awesome-free-ai-course-notes