Algorithms that learn through interaction with environments — from game AI to robotics control.
- David Silver's RL Course (DeepMind/UCL) - The classic RL course by the co-creator of AlphaGo, with videos and slides.
Intermediate - DeepMind x UCL: RL Lecture Series - Comprehensive, modern RL course from DeepMind researchers.
Intermediate - Coursera: Reinforcement Learning Specialization - University of Alberta specialization covering fundamentals to advanced algorithms.
Intermediate - Stanford CS234: Reinforcement Learning - Stanford's RL course with lecture videos, notes, and assignments.
Intermediate - Hugging Face: Deep RL Course - Hands-on course with interactive notebooks and model sharing.
Beginner - UC Berkeley CS285: Deep RL - Sergey Levine's deep RL course with full lecture videos.
Advanced
- Reinforcement Learning: An Introduction (Sutton & Barto) - The definitive RL textbook, freely available online.
Intermediate - OpenAI Spinning Up in Deep RL - Excellent educational resource with theory, code, and exercises.
Intermediate - Algorithms for Decision Making (MIT) - Free textbook covering decision-making under uncertainty.
Advanced
- OpenAI Gymnasium - Standard toolkit for developing and comparing RL algorithms.
All Levels - Stable-Baselines3 Documentation - Reliable RL algorithm implementations with great tutorials.
Intermediate - CleanRL - Single-file RL implementations that are easy to understand and modify.
Intermediate - PettingZoo - Multi-agent RL environment library.
Advanced