OpenAI Gym Training Course
OpenAI Gym serves as an open-source interface designed for the creation, development, and comparison of reinforcement learning (RL) tasks and algorithms. It offers a comprehensive collection of environment libraries that facilitate the effortless execution of reinforcement learning tasks.
This instructor-led live training, available either online or onsite, targets researchers and developers aiming to install, configure, customize, and implement OpenAI Gym to rapidly develop reinforcement learning algorithms.
Upon completing this training, participants will be equipped to build, develop, execute, and test reinforcement learning algorithms, thereby optimizing tasks and maximizing outcomes.
Course Format
- Interactive lectures and discussions.
- Numerous exercises and practical sessions.
- Hands-on implementation within a live-lab environment.
Course Customization Options
- To request customized training for this course, please contact us to make arrangements.
Course Outline
Introduction
Overview of OpenAI Gym Features and Architecture
Introduction to OpenAI Gym Basics
Exploring the OpenAI Gym Library
Installing OpenAI Gym and Its Dependencies
Building Gym Directly from Source
Working with OpenAI Gym Environments
Creating Custom Environments
Executing Environment Functions and Tasks
Managing Agents, Actions, Observations, and Rewards
Understanding Space Types in Environments
Utilizing OpenAI Gym’s Registry Function
Testing Algorithms and Environments
Troubleshooting
Summary and Conclusion
Requirements
- Proficiency in Python or other programming languages
- Familiarity with artificial intelligence (AI) and machine learning (ML) concepts
Audience
- Researchers
- Developers
Need help picking the right course?
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