Deep RL Course

Unit 0. Welcome to the course

Unit 1. Introduction to Deep Reinforcement Learning

Bonus Unit 1. Introduction to Deep Reinforcement Learning with Huggy

Live 1. How the course work, Q&A, and playing with Huggy

Unit 2. Introduction to Q-Learning

Unit 3. Deep Q-Learning with Atari Games

Bonus Unit 2. Automatic Hyperparameter Tuning with Optuna

Unit 4. Policy Gradient with PyTorch

Unit 5. Introduction to Unity ML-Agents

Unit 6. Actor Critic methods with Robotics environments

Introduction The Problem of Variance in Reinforce Advantage Actor Critic (A2C)Advantage Actor Critic (A2C) using Robotics Simulations with Panda-Gym 🤖Quiz Conclusion Additional Readings

Unit 7. Introduction to Multi-Agents and AI vs AI

Unit 8. Part 1 Proximal Policy Optimization (PPO)

Unit 8. Part 2 Proximal Policy Optimization (PPO) with Doom

Bonus Unit 3. Advanced Topics in Reinforcement Learning

Bonus Unit 5. Imitation Learning with Godot RL Agents

Certification and congratulations

Join the Hugging Face community

and get access to the augmented documentation experience

Collaborate on models, datasets and Spaces

Faster examples with accelerated inference

Switch between documentation themes

to get started

Conclusion

Congrats on finishing this unit and the tutorial. You’ve just trained your first virtual robots 🥳.

Take time to grasp the material before continuing. You can also look at the additional reading materials we provided in the additional reading section.

Finally, we would love to hear what you think of the course and how we can improve it. If you have some feedback then please 👉 fill out this form

See you in next unit!

Keep learning, stay awesome 🤗

Update on GitHub

←Quiz Additional Readings→