Deep Reinforcement Learning by Udacity

Develop advanced AI solutions with applications ranging from robotics to financial trading. To gain a foundation in AI techniques, you will implement classical solution methods, define Markov decision processes, policies, and value functions, and derive Bellman equations. Then, you will learn dynamic programming, Monte Carlo methods, temporal-difference methods, and deep reinforcement learning (deep RL) and apply these techniques to solve real-world problems. You will train agents to navigate virtual worlds, generate optimal financial trading strategies, and apply RL to multiple interacting agents.