Merge pull request #61 from huggingface/update/unit4

Update/unit4 with readme

unit4/README.md

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+# Unit 4: An Introduction to Unity MLAgents with Hugging Face 🤗
+![cover](https://miro.medium.com/max/1400/1*8DV9EFl-vdijvcTHilHuEw.png)
+
+In this Unit, We’ll learn about [ML-Agents](https://huggingface.co/docs/hub/ml-agents) and use one of the pre-made environments: Pyramids. In this environment, we’ll train an agent that needs to press a button to spawn a pyramid, then navigate to the pyramid, knock it over, and move to the gold brick at the top.
+
+To do that, **it will need to explore its environment, and we will use a technique called curiosity**.
+
+Then, after training we’ll push the **trained agent to the Hugging Face Hub and you’ll be able to visualize it playing directly on your browser without having to use the Unity Editor. You’ll be also be able to visualize and download others trained agents from the community**.
+
+![cover](https://raw.githubusercontent.com/huggingface/deep-rl-class/update/unit4/unit4/img/agents.gif)
+
+## Required time ⏱️
+The required time for this unit is, approximately:
+- 2 hours for the theory and hands-on.
+
+## Start this Unit 🚀
+Here are the steps for this Unit:
+
+1️⃣📖 **Read An [An Introduction to Unity ML-Agents with Hugging Face 🤗](https://thomassimonini.medium.com/an-introduction-to-unity-ml-agents-with-hugging-face-efbac62c8c80)**.
+
+2️⃣👩‍💻 In the meantime, **you can start the tutorial using Google Colab** 👉 [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/deep-rl-class/blob/main/unit4/unit4.ipynb)
+
+You can work directly **with the colab notebook, which allows you not to have to install everything on your machine (and it’s free)**.
+
+3️⃣ 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 etc**.
+
+## Additional readings 📚
+- [MLAgents Documentation](https://github.com/Unity-Technologies/ml-agents/blob/main/docs/Readme.md)
+
+## 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 fill this form** 👉 https://forms.gle/3HgA7bEHwAmmLfwh9
+
+## 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 🤗,

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