Learn the fundamentals of reinforcement learning (RL), where agents learn to make decisions by interacting with environments. This beginner-level course introduces foundational RL algorithms and models, enabling you to train agents using Q-Learning, Deep Q-Learning, Policy Gradients, Actor-Critic methods, Multi-Armed Bandits, and Inverse Reinforcement Learning.