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Hugging Face Deep RL Course

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The Hugging Face Deep Reinforcement Learning Course offers a comprehensive, free, and open-source learning experience. It covers both theoretical and practical aspects of Deep Reinforcement Learning, enabling learners to train agents in unique environments and participate in challenges.

  • Durationapproximately 3-4 hours per week per chapter
  • Modules8 units
  • PriceFree
  • CertificateYes
  • LevelBeginner to expert
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Hugging Face Deep RL Course screenshot
Hugging Face Deep RL Course screenshot

Welcome to the Hugging Face Deep Reinforcement Learning Course, an initiative aimed at advancing and democratizing artificial intelligence through open-source and open science. This course is designed to take you from beginner to expert in Deep Reinforcement Learning (RL), providing a solid foundation in both theory and practice.

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Throughout the course, you will study Deep Reinforcement Learning in depth, learning to utilize popular libraries such as Stable Baselines3, RL Baselines3 Zoo, Sample Factory, and CleanRL. You will have the opportunity to train agents in various unique environments, including SnowballFight, Huggy the Doggo, VizDoom, and classic games like Space Invaders and PyBullet. The course also encourages sharing your trained agents with the community and downloading powerful agents created by others.

One of the exciting aspects of this course is the participation in challenges where you can evaluate your agents against those of other teams. Completing 80% of the assignments will earn you a certificate of completion, while completing all assignments will grant you a certificate of honors. The course is self-paced, allowing you to learn at your own speed without any deadlines.

The course is structured into theoretical lessons and hands-on practical sessions, which are delivered through Google Colab notebooks. Each chapter is designed to be completed in approximately one week, with an estimated workload of 3-4 hours per week. Additionally, you can join study groups on Discord to enhance your learning experience and collaborate with fellow students.

Although the course is currently in a low-maintenance state, all theoretical content and practical exercises remain fully accessible and effective for learning. The course also includes a certification process that is completely free, allowing you to choose your path based on your learning goals. Whether you aim for a certificate of completion or simply wish to audit the course, you will find valuable resources and support throughout your journey in Deep Reinforcement Learning.

  • CategoryCorporate Training & E-Learning
  • Pricing ModelFree

  • Free and open-source course

  • Self-paced learning

  • Hands-on practical sessions

  • Certificate of completion available

  • Access to community-shared agents

  • Use of popular Deep RL libraries

  • Participation in challenges

  • No deadlines for course completion

  1. Study: Engage with theoretical content to understand Deep Reinforcement Learning concepts.

  2. Practice: Utilize Google Colab notebooks for hands-on training of agents.

  3. Participate: Join challenges to compete against other learners' agents.

  4. Collaborate: Join study groups on Discord for enhanced learning.

  • Learning Deep RL
  • Agent Training
  • Community Engagement
  • Participating in Challenges
  • Certification

From Hugging Face

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