Launching the v2.0 of Deep Reinforcement Learning Course with Hugging Face 🤗
Hey there👋 it’s Thomas Simonini from Hugging Face.
I’m super excited to announce the launch of the v2.0 Deep Reinforcement Learning Course with Hugging Face 🤗 starting on December the 5th. A course from beginner to expert.
After the first version from May to July 2022 with more than 5,000 students, we heard your feedback and we updated the course: adding more RL libraries, new environments such as Minecraft and Doom, and creating contests with our AI vs AI to compete with your trained agents against your classmates.
➡️➡️➡️ Register here for the free Hugging Face Deep Reinforcement Learning 🤗 course v2.0 👉🏻 http://eepurl.com/ic5ZUD
In this updated free course, you will:
- 📖 Study Deep Reinforcement Learning in theory and practice.
- 🧑💻 Learn to use famous Deep RL libraries such as Stable Baselines3, RL Baselines3 Zoo, Sample Factory, and CleanRL.
- 🤖 Train agents in unique environments such as SnowballFight, Huggy the Doggo 🐶, MineRL (Minecraft ⛏️), VizDoom (Doom), 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.
- 🏆 Participate in challenges where you will evaluate your agents against other teams. But also play against AI you’ll train.
- 🔈 Exchange with your classmates in our discord server 👉🏻 https://discord.gg/ydHrjt3WP5
- And more!
Let’s see in more detail what you’re going to do.
➡️➡️➡️ Register here for the free Hugging Face Deep Reinforcement Learning 🤗 course v2.0 👉🏻 http://eepurl.com/ic5ZUD
(We are collecting your email to send you the links when each Unit is published).
New libraries 📚
In this v2, you will learn to code some algorithms from scratch but also learn to use famous Deep RL libraries:
New Environments 🎮
You will learn to train agents to play in new exciting environments:
- Huggy the Doggo 🐶
- SnowballFight ⛄️
- MineRL (Minecraft ⛏️)
- VizDoom (Doom) 👽
- And classical ones such as Atari games with Space Invaders and robotics simulations with Mujoco and PyBullet.
Challenges AI vs AI🎮
In this course, you’re going to compare your agent’s results with other classmates using our updated leaderboard:
But the addition in this v2.0 is that for some environments you’ll be able to make them play against other’s classmates’ AI 😍
For instance, in Snowball fight, you’re going to try to beat other AIs:
We’re also building new competitive environments for this:
➡️➡️➡️ Register here for the free Hugging Face Deep Reinforcement Learning 🤗 course v2.0 👉🏻 http://eepurl.com/ic5ZUD
The Syllabus 📚
The Syllabus is published on our website here 👉🏻 https://simoninithomas.github.io/deep-rl-course/
How does the course work?
We publish one Unit every week, with two parts:
- A theory part where we will explain the topic deeply.
- A hands-on part where we use famous RL libraries to train our agents that we publish on Hub in one line of Code on the Hugging Face Hub.
- We also publish some bonus units that contain additional topics such as Multi-Agents, Offline RL, or Challenges like AI vs AI.
How to sign up?
📅 The course is starting on December the 5th
➡️➡️➡️ Register here for the free Hugging Face Deep Reinforcement Learning 🤗 course v2.0 👉🏻 http://eepurl.com/ic5ZUD
(We are collecting your email to send you the links when each Unit is published).
For now, you can sign up to our discord server to exchange with the community and with us 👉🏻 https://discord.gg/ydHrjt3WP5
I have some questions.
Please check our FAQ, and if you don’t find answers you can contact us on our Discord Server 🤗.
Back in April 2018, when I launched my first article about Introduction to RL I didn’t know that it would become one of the most-watched RL courses online and a GitHub repository with 3.400 GitHub stars. For that, I want to thank you.
I hope you will like this updated and improved version of the course. This is made for you. As a consequence, I’m always pleased to receive some feedback 📝.
If you want to help us, please like, share, and speak about our course. By sharing our articles and videos you help us to spread the word.
And don’t forget to share with your friends who want to learn 🤗 !
Keep Learning, and Stay Awesome 🤗
