AI that learns by doing. Master RL. Build agents that learn through trial, reward and strategy.
Hands-on with the learning paradigm behind game-playing AI, robotics and autonomous decision-making.
Train agents through trial and feedback.
Solve sequential decision problems.
The tech behind game and robotics breakthroughs.
Reinforcement Learning teaches the paradigm where AI learns by interacting with an environment — taking actions, receiving rewards and improving its strategy. Using Python and Gymnasium, you'll master the core concepts, from Markov decision processes and Q-learning to deep reinforcement learning — the technology behind game-playing AI, robotics and autonomous systems.
Python, ML & maths! Solid Python, machine learning and comfort with basic maths are recommended. This is an advanced course.
Earn the "Reinforcement Learning" badge upon completing all modules and the hands-on final assessment.
Verifiable CredentialAgents, environments, rewards and MDPs.
Q-learning and temporal-difference learning.
Policy gradients and actor-critic ideas.
Neural networks for complex problems.
Train an agent in a real environment.
Build agents that learn by doing.
Work at the frontier of AI.
Solve sequential decision problems.
Add RL to your advanced AI toolkit.
This is advanced — solid Python, machine-learning knowledge and comfort with basic maths are recommended. Our ML and Maths for ML courses are strong preparation.
A laptop; we use free tools — Python, Gymnasium and deep-learning libraries on Colab. Set-up help is provided.
To receive the Edmire Reinforcement Learning Certificate, complete all 5 modules and the capstone — a trained RL agent. Resubmission is free if needed.
Game-playing AI, robotics, autonomous vehicles, trading, recommendation and operations optimisation — anywhere an agent must make sequential decisions to maximise a goal.
Classroom training at our Dubai centre, live online instructor-led classes, or custom in-house delivery — with all materials yours to keep.
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