The Deep Reinforcement Learning Nanodegree has four courses: Introduction to Deep Reinforcement Learning, Value-Based Methods, Policy-Based Methods, and Multi-Agent RL. Students learn to implement classical solution methods, define Markov decision processes, policies, and value functions, and derive Bellman equations. They learn dynamic programming, Monte Carlo methods, temporal-difference methods
![Deep Reinforcement Learning Online Course](https://cdn-ak-scissors.b.st-hatena.com/image/square/83be1ad83c441b2b613bdd25fba07bddbaae53e1/height=288;version=1;width=512/https%3A%2F%2Fcdn.sanity.io%2Fimages%2Ftlr8oxjg%2Fproduction%2Fb72970b4e617777bc548c0f862be8d3ef1638d8c-1456x816.png%3Frect%3D128%2C93%2C1200%2C630)