The Hugging Face Deep Reinforcement Learning Class 🤗

In this free 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, and RLlib.
🤖 Train agents in unique environments such as SnowballFight, Huggy the Doggo 🐶, and classical ones such as Space Invaders and PyBullet.
💾 Publish your trained agents in one line of code to the Hugging Face Hub. But also download powerful agents from the community.
🏆 Participate in challenges where you will evaluate your agents against other teams.
🖌️🎨 Learn to share your own environments made with Unity and Godot.

➡️➡️➡️ Don't forget to sign up here: https://forms.gle/4bbgzs3oVZMjgDed7

The best way to keep in touch is to join our discord server to exchange with the community and with us 👉🏻 https://discord.gg/aYka4Yhff9

And don't forget to share with your friends who want to learn 🤗!

The Syllabus 🏗️

📆 Publishing date	📘 Unit	👩‍💻 Hands-on
May, the 4th	An Introduction to Deep Reinforcement Learning	Train a Deep Reinforcement Learning lander agent to land correctly on the Moon 🌕 using Stable-Baselines3
May, the 11th	Bonus	🎁 it's a surprise 🎁
May, the 18th	Q-Learning	Train an agent to cross a Frozen lake in this new version of the environment.
June, the 1st	Deep Q-Learning and improvements	Train a Deep Q-Learning agent to play Space Invaders
	Policy-based methods	🏗️
	Actor-Critic Methods	🏗️
	Proximal Policy Optimization (PPO)	🏗️
	Decision Transformers and offline Reinforcement Learning	🏗️
	Towards better explorations methods	🏗️