Reinforcement Learning

Reinforcement Learning is a type of Machine Learning where an agent learns to make decisions by taking actions in an environment to maximize a reward. Coursera's Reinforcement Learning catalogue teaches you the foundational principles and algorithms of reinforcement learning. You'll understand the exploration-exploitation tradeoff, learn about Markov Decision Processes (MDPs), and explore different methods for value function approximation. You'll also learn how to implement various reinforcement learning algorithms such as Q-Learning, Policy Gradient methods, and Deep Q-Networks (DQN). The understanding gained from these courses will equip you to handle complex real-world problems like game playing, robotics, navigation, and more.