Adding Unit 2 bases

unit2/README.md

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+# Unit 2: Introduction to Q-Learning
+
+In this Unit, we're going to dive deeper into one of the Reinforcement Learning methods: value-based methods and **study our first RL algorithm: Q-Learning**.
+
+We'll also implement our **first RL agent from scratch**: a Q-Learning agent and will train it in two environments:
+
+- Frozen-Lake-v1 ⛄ (non-slippery version): where our agent will need to go from the starting state (S) to the goal state (G) by walking only on frozen tiles (F) and avoiding holes (H).
+- An autonomous taxi 🚕 will need to learn to navigate a city to transport its passengers from point A to point B.
+
+<img src="assets/img/envs.gif" alt="unit 2 environments"/>
+
+You'll then be able to **compare your agent’s results with other classmates thanks to a leaderboard** 🔥.
+
+This Unit is divided into 2 parts:
+- Part 1 is published
+- Part 2 will be published on Friday 📅
+
+<img src="assets/img/two_parts.jpg" alt="Two parts"/>
+
+
+
+This course is **self-paced**, you can start whenever you want.
+
+## Required time ⏱️
+The required time for this unit is, approximately:
+- 2-3 hours for the theory
+- 1 hour for the hands-on.
+
+## Start this Unit 🚀
+Here are the steps for this Unit:
+
+1️⃣  If it's not already done, sign up to our Discord Server. This is the place where you **can exchange with the community and with us, create study groups to grow each other and more** 
+
+👉🏻 [https://discord.gg/aYka4Yhff9](https://discord.gg/aYka4Yhff9).
+
+Are you new to Discord? Check our **discord 101 to get the best practices** 👉 https://github.com/huggingface/deep-rl-class/blob/main/DISCORD.Md
+
+2️⃣ **Introduce yourself on Discord in #introduce-yourself Discord channel 🤗 and check on the left the Reinforcement Learning section.**
+
+- In #rl-announcements we give the last information about the course.
+- #discussions is a place to exchange.
+- #unity-ml-agents is to exchange about everything related to this library.
+- #study-groups, to create study groups with your classmates.
+
+<img src="assets/img/discord_channels.jpg" alt="Discord Channels"/>
+
+3️⃣ 📖 **Read An [Introduction to Q-Learning Part 1](https://huggingface.co/blog/deep-rl-q-part1)**.
+
+## Additional readings 📚
+- [Reinforcement Learning: An Introduction, Richard Sutton and Andrew G. Barto Chapter 5, 6 and 7](http://incompleteideas.net/book/RLbook2020.pdf)
+- [Foundations of Deep RL Series, L2 Deep Q-Learning by Pieter Abbeel](https://youtu.be/Psrhxy88zww)
+
+
+## How to make the most of this course
+
+To make the most of the course, my advice is to:
+
+- **Participate in Discord** and join a study group.
+- **Read multiple times** the theory part and takes some notes
+- Don’t just do the colab. When you learn something, try to change the environment, change the parameters and read the libraries' documentation. Have fun 🥳
+- Struggling is **a good thing in learning**. It means that you start to build new skills. Deep RL is a complex topic and it takes time to understand. Try different approaches, use our additional readings, and exchange with classmates on discord.
+
+## This is a course built with you 👷🏿‍♀️
+
+We want to improve and update the course iteratively with your feedback. If you have some, please open an issue on the Github Repo: [https://github.com/huggingface/deep-rl-class/issues](https://github.com/huggingface/deep-rl-class/issues)
+
+## Don’t forget to join the Community 📢
+
+We have a discord server where you **can exchange with the community and with us, create study groups to grow each other and more** 
+
+👉🏻 [https://discord.gg/aYka4Yhff9](https://discord.gg/aYka4Yhff9).
+
+Don’t forget to **introduce yourself when you sign up 🤗**
+
+❓If you have other questions, [please check our FAQ](https://github.com/huggingface/deep-rl-class#faq)
+
+Keep learning, stay awesome,