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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 16:17:16 +01:00
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@@ -43,7 +43,7 @@ The course is composed of:
- *A theory part*: where you learn a **concept in theory (article)**.
- *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*: such AI vs. AI and leaderboard.
- *Challenges*: you'll get to put your agent to compete against other agents in different challenges. There will also be leaderboards for you to compare the agents' performance.
## Two paths: choose your own adventure [[two-paths]]