Introduction to Reinforcement Learning

This intensive mini-bootcamp offers a comprehensive introduction to reinforcement learning through practical exercises. It begins with fundamental Python and PyTorch programming, progresses to constructing RL environments, and culminates in solving them using algorithms spanning classical RL to deep RL. Topics include DQN and REINFORCE, presented in a structured manner with increasing difficulty levels. Each session concludes with a dedicated notebook for hands-on practice and application of theoretical concepts.