Module 1: RL Components

In this module, we will explain what types of problems can be solved with reinforcement learning (RL), as well as the terminology we'll need for the rest of the course.

0Module 1 Learning Outcomes

1Supervised learning vs. reinforcement learning

2Supervised learning or reinforcement learning

3Frozen Lake preview

4RL Environments

5Self-driving car environment

6Episodes vs. time steps

7Observations vs. renderings

8RL Policies

9Frozen Lake policy

10Computing expected reward

11Hand-crafted policy

About this course

This course teaches you the basics of reinforcement learning in an applied fashion, by leveraging the production-grade RL framework Ray RLlib. Enjoy!

About the team

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