Learn Reinforcement Learning with Gymnasium
Learn reinforcement learning fundamentals and build learning agents with Gymnasium in this hands-on Python course.
Skill level
IntermediateTime to complete
Average based on combined completion rates — individual pacing in lessons, projects, and quizzes may vary2 hoursProjects
2Prerequisites
2 coursesWe suggest you complete the following courses before you get started with Learn Reinforcement Learning with Gymnasium:- Learn Intermediate Python 3
- Learn Python 3
About this course
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.
Skills you'll gain
Build learning agents using reinforcement learning algorithms
Implement Q-learning and SARSA using Python and Gymnasium
Design and customize your own RL environments in Gymnasium
Apply Monte Carlo methods to learn from episodic experiences
Simulate and solve classic RL problems like CartPole, FrozenLake, Twenty-One, and multi-armed bandits
Syllabus
2 lessons • 2 projects • 2 quizzesCertificate of completion available with Plus or Pro
Earn a certificate of completion and showcase your accomplishment on your resume or LinkedIn.
Projects in this course
- practice Project
Solve Twenty-One with Reinforcement Learning
Train reinforcement learning agents to play Twenty-One using Q-learning and SARSA algorithms with Python and Gymnasium - practice Project
Solve Cart Pole with Reinforcement Learning
Train reinforcement learning agents to play CartPole using Monte Carlo algorithms with Python and Gymnasium.
Earn a certificate of completion
Show your network you've done the work by earning a certificate of completion for each course or path you finish.- Show proofReceive a certificate that demonstrates you've completed a course or path.
- Build a collectionThe more courses and paths you complete, the more certificates you collect.
- Share with your networkEasily add certificates of completion to your LinkedIn profile to share your accomplishments.
Reviews from learners
- The progress I have made since starting to use codecademy is immense! I can study for short periods or long periods at my own convenience - mostly late in the evenings.ChrisCodecademy Learner @ USA
- I felt like I learned months in a week. I love how Codecademy uses learning by practice and gives great challenges to help the learner to understand a new concept and subject.RodrigoCodecademy Learner @ UK
- Brilliant learning experience. Very interactive. Literally a game changer if you're learning on your own.John-AndrewCodecademy Learner @ USA
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Frequently asked questions about Reinforcement Learning with Gymnasium
Reinforcement learning is a type of machine learning where agents learn through trial and error by interacting with an environment. Unlike supervised learning that uses labeled data, RL agents discover optimal strategies by receiving rewards or penalties based on their actions.
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Related resources
- Article
What is Reinforcement Learning? With Examples
Learn the basics of reinforcement learning with its types, advantages, disadvantages, and applications. - Article
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Practice Projects
Guided projects that help you solidify the skills and concepts you're learning.Assessments
Auto-graded quizzes and immediate feedback help you reinforce your skills as you learn.Certificate of Completion
Earn a document to prove you've completed a course or path that you can share with your network.