Enroll Course: https://www.coursera.org/learn/dmrol
If you’re interested in understanding how machines and algorithms make decisions, the ‘Decision Making and Reinforcement Learning’ course on Coursera is an excellent starting point. Led by Professor Tony Dear, this course offers a comprehensive introduction to the fundamental concepts of sequential decision making, utility theory, and reinforcement learning. It begins with the basics of utility theory, helping learners understand how preferences can be modeled for decision making. The course then delves into multi-armed bandit problems, which exemplify the challenge of balancing exploration and exploitation to maximize rewards. As the course progresses, students explore Markov Decision Processes (MDPs) and gain hands-on knowledge of dynamic programming algorithms used to solve complex decision problems. The structure is accessible for beginners yet rich enough to provide valuable insights for those looking to deepen their understanding of AI, machine learning, and decision sciences. I highly recommend this course to students, professionals, and enthusiasts eager to explore the fascinating world of reinforcement learning and improve their decision-making skills in both theoretical and practical contexts.
Enroll Course: https://www.coursera.org/learn/dmrol