OpenAI Gym Training Course
OpenAI Gym serves as an open-source interface designed for creating, developing, and comparing reinforcement learning (RL) tasks and algorithms. It offers a comprehensive suite of environment libraries that facilitate the execution of reinforcement learning tasks with ease.
This instructor-led live training, available either online or onsite, is specifically targeted at researchers and developers who intend to install, configure, customize, and implement OpenAI Gym to rapidly develop reinforcement learning algorithms.
Upon completing this training, participants will be equipped with the skills to build, develop, execute, and test reinforcement learning algorithms, thereby optimizing tasks to achieve optimal 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
Introduction
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
Troubleshooting
Summary and Conclusion
Requirements
- Knowledge of Python or other programming languages
- Understanding of artificial intelligence (AI) and machine learning (ML) concepts
Audience
- Researchers
- Developers
Need help picking the right course?
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OpenAI Gym Training Course - Enquiry
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