From 044f4852e93ff556dcc1ada2080ff742ec69f6d2 Mon Sep 17 00:00:00 2001
From: Thomas Simonini <simonini.thomas.pro@gmail.com>
Date: Thu, 21 Apr 2022 13:34:08 +0200
Subject: [PATCH] Update README.md

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-# deep-rl-bootcamp
-This repo will contain the syllabus of the Hugging Face Deep Reinforcement Learning Bootcamp.
+# The Hugging Face Deep Reinforcement Learning Bootcamp 🤗
+
+In this free bootcamp, 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 Hub**. But also **download powerful agents from the community**.
+
+➡️➡️➡️ 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
+
+# Unit 1: An Introduction to Deep Reinforcement Learning
+  - Theory: An Introduction to Deep Reinforcement Learning
+  - Hands-on: Train your first agent with SB3
+
+# Bonus: Train Huggy the Doggo
+
+# Unit 2: Q-Learning
+
+# Unit 3: Deep Q-Learning and improvements
+
+
+# Unit 4: Policy based methods
+
+
+# Unit 5: Actor Critic Methods
+
+
+# Unit 6: Proximal Policy Optimization (PPO)
+
+
+# Unit 7: Decision Transformers 
+
+
+- Introduction to Deep Reinforcement Learning
+    - Theory: C1 DRLC Introduction to Deep RL
+    - Practice: Lunar Lander
+    - Library: SB3
+    - Bonus: Huggy
+
+- Value based methods: Q-Learning
+    - Theory: Q-Learning
+    - Practice: Frozen lake updated version
+
+- Deep Q-Learning and improvements
+    - Theory: Deep Q-Learning and DDQN
+    - Practice:
+