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Updated in [July 21st, 2023]
This course provides an introduction to Reinforcement Learning (RL) using Python, OpenAI Gym and Stable Baselines. It covers all the fundamentals required to get started with RL, including how to build deep learning powered agents to solve a variety of RL problems. Participants will learn how to build custom environments using OpenAI Gym, and how to work on custom projects for RL. The course also covers topics such as loading OpenAI Gym environments, training RL models, saving and reloading environments, evaluating and testing RL models, performance tuning, adding training callbacks, changing policies and algorithms, and building custom OpenAI Gym environments. By the end of the course, participants will have the skills and knowledge to create their own RL projects.