This course introduces Deep Reinforcement Learning (DRL), an emerging field combining deep learning and reinforcement learning to create intelligent agents that learn through trial and error. Students will learn the fundamentals of DRL, including core concepts, algorithms, and architectures used to build and train deep reinforcement learning models. The course also covers neural networks like CNNs and RNNs. Students will gain hands-on experience applying these techniques to real-world AI problems.
Prerequisite Courses