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@@ -7,6 +7,7 @@ In this free course, you will:
- 🤖 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
@@ -15,10 +16,10 @@ The best way to keep in touch is to **join our discord server to exchange with t
And don't forget to share with your friends who want to learn 🤗!
## The Syllabus 🏗️
| 📆 | 📘 Unit | 👩‍💻 Hands-on |
| 📆 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 | Train Huggy the Doggo to catch the stick |
| May, the 11th | Bonus | 🎁 it's a suprise 🎁 |
| 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 | 🏗️ |