Deep Reinforcement Learning

This course introduces deep reinforcement learning (RL), a cutting-edge technique in machine learning that has rapidly gained attention from researchers and developers due to its vast range of applications. Deep RL is making significant contributions in fields such as autonomous robotics, minimally invasive robotic surgery, advanced pattern recognition, diagnostic imaging, clinical decision support systems, personalized medical treatments, drug discovery processes, natural language understanding, speech recognition, and computer vision. Deep RL is often considered the third paradigm of machine learning, alongside supervised and unsupervised algorithms. In deep RL, an agent learns as a result of its actions and interactions with the environment, typically without the need for external guidance. Historically, practical applications of RL have been challenging, but recent advancements have made it more accessible and practical. This course provides students with both a theoretical understanding and practical experience in deploying deep RL solutions.