Course Resources
Required Textbook
Reinforcement Learning: An Introduction by Sutton & Barto
The definitive textbook on RL fundamentals
Access free online version →Supplementary Video Courses
- David Silver's RL Course — UCL
Classic RL course with comprehensive video lectures
- Berkeley Deep RL Course — UC Berkeley
Advanced deep RL with practical implementations
Essential Papers
Foundation Papers
RLHF & Language Models
Policy Gradient Methods
Software Tools & Libraries
Recommended Blogs
Getting Started
- • Prerequisites: Python proficiency, basic ML knowledge, calculus/linear algebra
- • Environment Setup: Use Google Colab for free GPU access or set up local environment
- • Community: Join RL communities on Reddit, Discord, or Stack Overflow for discussions
- • Practice: Start with simple environments before tackling complex projects