All resources(e.g. lecture slides) in here.

Lecture 1. Introduction

Lecture 2: Imitation Learning

Lecture 3. PyTorch and Neural Nets

Lecture 4. Introduction to Reinforcement Learning

Lecture 5. Policy Gradients

Lecture 6. Actor-Critic Algorithms

Lecture 7. Value Function Methods

Lecture 8. Deep RL with Q-Functions

Lecture 10. Optimal Control and Planning

Lecture 13. Exploration (Pt.1)