Learn Reinforcement Learning with Gymnasium

Reinforcement learning is used in breakthrough AI applications, from game-playing systems to autonomous vehicles navigating complex environments. This reinforcement learning course teaches you to build agents that learn through trial and error. You'll master core concepts like the agent-environment loop, reward systems, and policy optimization through hands-on Python projects using Gymnasium. Unlike supervised learning that relies on labeled data, reinforcement learning with Gymnasium lets you create agents that discover optimal strategies by interacting with their environment and maximizing cumulative rewards over time.

Syllabus

Intro to Reinforcement Learning: Build reinforcement learning agents using Python and Gymnasium. Explore rewards, policies, and key algorithms, such as Q-learning and SARSA.

Lesson: Intro to Reinforcement Learning
Project: Solve Twenty-One with Reinforcement Learning
Quiz: Intro to Reinforcement Learning Quiz