# Unit 1: Introduction to Deep Reinforcement Learning In this Unit, you'll learn the foundations of Deep RL. And **you’ll train your first lander agent 🚀 to land correctly on the Moon 🌕** using Stable-Baselines3 and share it with the community. LunarLander You'll then be able to **compare your agent’s results with other classmates thanks to a leaderboard** 🔥. This course is **self-paced**, you can start whenever you want. ## Required time ⏱️ The required time for this unit is, approximately: - 2 hours for the theory - 1 hour for the hands-on. ## Start this Unit 🚀 Here are the steps for this Unit: 1️⃣ 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. Discord Channels 3️⃣ 📖 **Read An [Introduction to Deep Reinforcement Learning](https://huggingface.co/blog/deep-rl-intro)**, where you’ll learn the foundations of Deep RL. You can also watch the video version attached to the article. 👉 https://huggingface.co/blog/deep-rl-intro 4️⃣ 📝 Take a piece of paper and **check your knowledge with this series of questions** ❔ 👉 https://github.com/huggingface/deep-rl-class/blob/main/unit1/quiz.md 5️⃣ 👩‍💻 Then dive on the hands-on, where **you’ll train your first lander agent 🚀 to land correctly on the Moon 🌕 using Stable-Baselines3 and share it with the community.** Thanks to a leaderboard, **you'll be able to compare your results with other classmates** and exchange the best practices to improve your agent's scores Who will win the challenge for Unit 1 🏆? The hands-on 👉 [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/deep-rl-class/blob/main/unit1/unit1.ipynb) The leaderboard 👉 https://huggingface.co/spaces/chrisjay/Deep-Reinforcement-Learning-Leaderboard You can work directly **with the colab notebook, which allows you not to have to install everything on your machine (and it’s free)**. 6️⃣ The best way to learn **is to try things on your own**. That’s why we have a challenges section in the colab where we give you some ideas on how you can go further: using another environment, using another model etc. ## Additional readings 📚 - [Reinforcement Learning: An Introduction, Richard Sutton and Andrew G. Barto Chapter 1, 2 and 3](http://incompleteideas.net/book/RLbook2020.pdf) - [Foundations of Deep RL Series, L1 MDPs, Exact Solution Methods, Max-ent RL by Pieter Abbeel](https://youtu.be/2GwBez0D20A) - [Spinning Up RL by OpenAI Part 1: Key concepts of RL](https://spinningup.openai.com/en/latest/spinningup/rl_intro.html) - [Getting Started With OpenAI Gym: The Basic Building Blocks](https://blog.paperspace.com/getting-started-with-openai-gym/) ## 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,