Courses
Course reviews, notes, and cheat sheets for some classes I particularly enjoyed.
| Course | Difficulty | Fun |
|---|---|---|
| Graduate & seminars | ||
| CS 185/285 · Deep Reinforcement Learning | ||
| CS 280 · Graduate Computer Vision | ||
| CS 288 · Advanced NLP | ||
| CS 294-318 · VLA Seminar † | ||
| CS 294-288 · Data-Centric LLMs Seminar * | ||
| EE 226A · Measure Theory & Stochastic Processes * | ||
| Stanford CS 336 · Language Modeling from Scratch † | ||
| MIT 6.S184 · Diffusion & Flow Matching † | ||
| Robotics & control | ||
| EECS 106A · Robotics | ||
| EECS 116 · Robot Navigation * | ||
| EE C128 · Linear Control * | ||
| ML, vision & language | ||
| CS 180 · Computer Vision | ||
| EECS 183 · Natural Language Processing ‡ | ||
| CS 182 · Deep Learning † | ||
| CS 189 · Machine Learning | ||
| CS 188 · Artificial Intelligence | ||
| EE 194-16 · Scalable AI † | ||
| CS 194-196 · Agentic AI | ||
| CDSS 94 · Post-training Seminar | ||
| Math | ||
| EECS 126 · Probability & Random Processes | ||
| EECS 127 · Convex Optimization | ||
| CS 70 · Discrete Math & Probability ‡ | ||
* in progress † audit ‡ teaching