Deep Reinforcement Learning Course

Overview

Welcome to the most fascinating topic in Artificial Intelligence: Deep Reinforcement Learning.

This course will teach you about Deep Reinforcement Learning from beginner to expert. It’s completely free and open-source!

In this introduction unit you’ll:

Learn more about the course content.
Define the path you’re going to take (either self-audit or certification process).
Learn more about the AI vs. AI challenges you’re going to participate in.
Learn more about us.
Create your Hugging Face account (it’s free).
Sign-up to our Discord server, the place where you can chat with your classmates and us (the Hugging Face team).

Let’s get started!

What to expect?

In this course, you will:

📖 Study Deep Reinforcement Learning in theory and practice.
🧑‍💻 Learn to use famous Deep RL libraries such as Stable Baselines3, RL Baselines3 Zoo, Sample Factory and CleanRL.
🤖 Train agents in unique environments such as SnowballFight, Huggy the Doggo 🐶, VizDoom (Doom) and classical ones such as Space Invaders, PyBullet and more.
💾 Share your trained agents with one line of code to the Hub and also download powerful agents from the community.
🏆 Participate in challenges where you will evaluate your agents against other teams. You’ll also get to play against the agents you’ll train.
🎓 Earn a certificate of completion by completing 80% of the assignments.

And more!

At the end of this course, you’ll get a solid foundation from the basics to the SOTA (state-of-the-art) of methods.

Don’t forget to sign up to the course (we are collecting your email to be able to send you the links when each Unit is published and give you information about the challenges and updates).

What does the course look like?

The course is composed of:

A theory part: where you learn a concept in theory.
A hands-on: where you’ll learn to use famous Deep RL libraries to train your agents in unique environments. These hands-on will be Google Colab notebooks with companion tutorial videos if you prefer learning with video format!
Challenges: you’ll get to put your agent to compete against other agents in different challenges. There will also be a leaderboard for you to compare the agents’ performance.