Reinforcement Learning Specialization
Course Features
Duration
5 months
Delivery Method
Online
Available on
Limited Access
Accessibility
Desktop, Laptop
Language
English
Subtitles
English
Level
Intermediate
Effort
4 hours per week
Teaching Type
Self Paced
Course Description
Course Overview
International Faculty
Post Course Interactions
Instructor-Moderated Discussions
Skills You Will Gain
What You Will Learn
Build a Reinforcement Learning system for sequential decision making
Understand the space of RL algorithms (Temporal- Difference learning, Monte Carlo, Sarsa, Q-learning, Policy Gradients, Dyna, and more)
Understand how to formalize your task as a Reinforcement Learning problem, and how to begin implementing a solution
Understand how RL fits under the broader umbrella of machine learning, and how it complements deep learning, supervised and unsupervised learning
Course Instructors
Martha White
Assistant Professor