Reinforcement Learning Certification Course Overview
In this course, you will be introduced to Reinforcement Learning, an area of Machine Learning. You will learn the Markov Decision Processes, Bandit Algorithms, Dynamic Programming, and Temporal Difference (TD) methods. You will be introduced to Value function, Bellman Equation, and Value iteration. You will also learn Policy Gradient methods. You will learn to make decisions in uncertain environment.
Learning Objectives:
- To introduce you to the fundamentals of Reinforcement Learning and its elements.
- Introduce you to OpenAI Gym - a programming environment used for implementing RL agents.
- To learn Bandit Algorithms and Markov Decision Process.
- To develop an understanding of Dynamic Programming Algorithms and Temporal Difference Learning methods.
- To learn Policy Gradients and develop an understanding of Deep Q Learning.
- To provide you hands-on experience in Reinforcement Learning.