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Update units/en/unit0/introduction.mdx

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Co-authored-by: Omar Sanseviero <osanseviero@gmail.com>
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Thomas Simonini
2022-12-04 16:14:24 +01:00
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@@ -24,7 +24,7 @@ In this course, you will:
- 📖 Study Deep Reinforcement Learning in **theory and practice.**
- 🧑‍💻 Learn to **use famous Deep RL libraries** such as [Stable Baselines3](https://stable-baselines3.readthedocs.io/en/master/), [RL Baselines3 Zoo](https://github.com/DLR-RM/rl-baselines3-zoo), [Sample Factory](https://samplefactory.dev/) and [CleanRL](https://github.com/vwxyzjn/cleanrl).
- 🤖 **Train agents in unique environments** such as [SnowballFight](https://huggingface.co/spaces/ThomasSimonini/SnowballFight), [Huggy the Doggo 🐶](https://huggingface.co/spaces/ThomasSimonini/Huggy), [MineRL (Minecraft ⛏️)](https://minerl.io/), [VizDoom (Doom)](https://vizdoom.cs.put.edu.pl/) and classical ones such as [Space Invaders](https://www.gymlibrary.dev/environments/atari/) and [PyBullet](https://pybullet.org/wordpress/).
- 💾 Publish your **trained agents with one line of code to the Hub**. But also download powerful agents from the community.
- 💾 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. But also play against AI you'll train.**
And more!