OpenAI Gym Training Course


7 hours (usually 1 day including breaks)


  • Knowledge of Python or other programming languages
  • Understanding of artificial intelligence (AI) and machine learning (ML) concepts


  • Researchers
  • Developers


OpenAI Gym is an open-source interface used to create, develop, and compare reinforcement learning (RL) tasks and algorithms. Gym provides a wide set of environment libraries to run reinforcement learning tasks with ease.

This instructor-led, live training (online or onsite) is aimed at researchers and developers who wish to install, configure, customize, and implement OpenAI Gym to quickly develop reinforcement learning algorithms.

By the end of this training, participants will be able to build, develop, execute, and test reinforcement learning algorithms to optimize tasks and achieve maximum results.

Format of the Course

  • Interactive lecture and discussion.
  • Lots of exercises and practice.
  • Hands-on implementation in a live-lab environment.

Course Customization Options

  • To request a customized training for this course, please contact us to arrange.

Course Outline


Overview of OpenAI Gym Features and Architecture

Learning About OpenAI Gym Basics

Exploring the OpenAI Gym Library

Installing OpenAI Gym and Dependencies

Building Gym Directly from Source

Working with OpenAI Gym Environments

Creating Your Own Environments

Executing Environment Functions and Tasks

Working with Agents, Actions, Observations, and Rewards

Understanding Space Types in Environments

Using OpenAI Gym’s Registry Function

Testing the Algorithms and Environments


Summary and Conclusion

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