Course Notes
Courses I am taking or have taken at UC Berkeley.
Machine Learning & AI
CS 185 — Deep Reinforcement Learning
Taught by Sergey Levine.
EECS 183 — Natural Language Processing
Taught by Gopala Anumanchipalli and Alane Suhr.
CDSS 94 — Post-Training AI Systems
Learned a lot with Karina Nguyen and Kevin Miao.
Mathematics & Theory
Math 54 — Linear Algebra and Differential Equations
Taught by Zvezdelina Stankova.
Math 55 — Discrete Mathematics
Taught by James Demmel.
Math 110 — Linear Algebra
Taught by Olga Holtz.
Math 113 — Introduction to Abstract Algebra
Taught by Ken Ribet.
Math 128A — Numerical Analysis
Taught by Per-Olof Persson.
EECS 126 — Probability and Random Processes
Taught by Kannan Ramchandran.
EECS 127 — Optimization Models in Engineering
Taught by Gireeja Ranade.
Entrepreneurship
UGBA 195T — Startup Relationships
Learning from Jules has changed my life for the better. I’m truly grateful to have been his student, and I hope to become an investor or entrepreneur one day.
Self-Study
Deep RL Bootcamp · lectures
OpenAI Spinning Up · RL notes
The Ultra-Scale Playbook · distributed training
veRL · RL post-training systems
OpenRLHF · RLHF framework
RLHF Book · post-training notes