# [Deep Reinforcement Learning Course](https://simoninithomas.github.io/deep-rl-course/) # ⚠️ The new version of Deep Reinforcement Learning Course starts on October the 2nd 2020. [➡️ More info here ⬅️](https://medium.com/deep-reinforcement-learning-course/launching-deep-reinforcement-learning-course-v2-0-38fa3c24bcbc) Deep Reinforcement Course with Tensorflow and PyTorch

Deep Reinforcement Course with Tensorflow and PyTorch

# Syllabus
## Chapter 1: Introduction to Deeep Reinforcement Learning ### 📜 [ARTICLE Introduction to Deep Reinforcement Learning](https://medium.com/@thomassimonini/an-introduction-to-deep-reinforcement-learning-17a565999c0c?source=friends_link&sk=1b1121ae5d9814a09ca38b47abc7dc61)

### 📹 [VIDEO Introduction to Deep Reinforcement Learning](https://youtu.be/q0BiUn5LiBc) ## Chapter 2: Q-learning with Taxi-v3 🚕
### 📜 [ARTICLE: Q-Learning, let’s create an autonomous Taxi 🚖 (Part 1/2)](https://medium.com/@thomassimonini/q-learning-lets-create-an-autonomous-taxi-part-1-2-3e8f5e764358) ### [VIDEO Q-Learning, let’s create an autonomous Taxi 🚖 (Part 1/2)](https://youtu.be/230bR2DrbdE) ### 📹 [ARTICLE: Q-Learning, let’s create an autonomous Taxi 🚖 (Part 2/2)] 📅Friday📅 ### 📹 [VIDEO: Q-Learning, let’s create an autonomous Taxi 🚖 (Part 2/2)] 📅Friday📅 ### [FROZENLAKE IMPLEMENTATION](https://github.com/simoninithomas/Deep_reinforcement_learning_Course/raw/master/Q%20learning/FrozenLake/Q%20Learning%20with%20FrozenLake.ipynb)
### 📹 [Implementing a Q-learning agent that plays Taxi-v2 🚕](https://youtu.be/q2ZOEFAaaI0)

## Part 3: Deep Q-learning with Doom
### 📜 [ARTICLE](https://medium.freecodecamp.org/an-introduction-to-deep-q-learning-lets-play-doom-54d02d8017d8) // [DOOM IMPLEMENTATION](https://github.com/simoninithomas/Deep_reinforcement_learning_Course/raw/master/Deep%20Q%20Learning/Doom/Deep%20Q%20learning%20with%20Doom.ipynb)
### 📹 [Create a DQN Agent that learns to play Atari Space Invaders 👾](https://youtu.be/gCJyVX98KJ4)

## Part 4: Policy Gradients with Doom
### 📜 [ARTICLE](https://medium.freecodecamp.org/an-introduction-to-policy-gradients-with-cartpole-and-doom-495b5ef2207f) // [CARTPOLE IMPLEMENTATION](https://github.com/simoninithomas/Deep_reinforcement_learning_Course/raw/master/Policy%20Gradients/Cartpole/Cartpole%20REINFORCE%20Monte%20Carlo%20Policy%20Gradients.ipynb) // [DOOM IMPLEMENTATION](https://github.com/simoninithomas/Deep_reinforcement_learning_Course/raw/master/Policy%20Gradients/Doom/Doom%20REINFORCE%20Monte%20Carlo%20Policy%20gradients.ipynb)
### 📹 [Create an Agent that learns to play Doom deathmatch](https://www.youtube.com/watch?v=wLTQRuizVyE)

## Part 3+: Improvments in Deep Q-Learning
### 📜 [ARTICLE](https://medium.freecodecamp.org/improvements-in-deep-q-learning-dueling-double-dqn-prioritized-experience-replay-and-fixed-58b130cc5682)// [Doom Deadly corridor IMPLEMENTATION](https://github.com/simoninithomas/Deep_reinforcement_learning_Course/raw/master/Dueling%20Double%20DQN%20with%20PER%20and%20fixed-q%20targets/Dueling%20Deep%20Q%20Learning%20with%20Doom%20(%2B%20double%20DQNs%20and%20Prioritized%20Experience%20Replay).ipynb)
### 📹 [Create an Agent that learns to play Doom Deadly corridor](https://youtu.be/-Ynjw0Vl3i4)

## Part 5: Advantage Advantage Actor Critic (A2C)
### 📜 [ARTICLE](https://medium.freecodecamp.org/an-intro-to-advantage-actor-critic-methods-lets-play-sonic-the-hedgehog-86d6240171d)
### 📹 [Create an Agent that learns to play Sonic](https://youtu.be/GCfUdkCL7FQ)

## Part 6: Proximal Policy Gradients
### 📜 [ARTICLE](https://towardsdatascience.com/proximal-policy-optimization-ppo-with-sonic-the-hedgehog-2-and-3-c9c21dbed5e)
### 👨‍💻 [Create an Agent that learns to play Sonic the Hedgehog 2 and 3 ](https://github.com/simoninithomas/Deep_reinforcement_learning_Course/tree/master/PPO%20with%20Sonic%20the%20Hedgehog)

## Part 7: Curiosity Driven Learning made easy Part I

### 📜 [ARTICLE](https://towardsdatascience.com/curiosity-driven-learning-made-easy-part-i-d3e5a2263359)

## Part 8: Random Network Distillation with PyTorch
## 👨‍💻 [A trained RND agent that learned to play Montezuma's revenge (21 hours of training with a Tesla K80](https://github.com/simoninithomas/Deep_reinforcement_learning_Course/tree/master/RND%20Montezuma's%20revenge%20PyTorch)

## Any questions 👨‍💻

If you have any questions, feel free to ask me:

📧: simonini.thomas.pro@gmail.com

Github: https://github.com/simoninithomas/Deep_reinforcement_learning_Course

🌐 : https://simoninithomas.github.io/deep-rl-course/

Twitter: @ThomasSimonini

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