Fundamentals of Reinforcement Learning

The Reinforcement Learning Specialization consists of 4 courses exploring the power of adaptive learning systems and artificial intelligence (AI).Harnessing the full potential of artificial intelligence requires adaptive learning systems. Learn how Reinforcement Learning (RL) solutions help solve real-world problems through trial-and-error interaction by implementing a complete RL solution from beginning to end.By the end of this Specialization, learners will understand the foundations of much of modern probabilistic artificial intelligence (AI) and be prepared to take more advanced courses or

( 109 Reviews )

Created by: Martha White

Quality Score

Content Quality

Video Quality

Qualified Instructor

Course Pace

Course Depth & Coverage

Overall Score : 94 / 100

Course Description

Reinforcement Learning is a subfield of Machine Learning, but is also a general purpose formalism for automated decision-making and AI. This course introduces you to statistical learning techniques where an agent explicitly takes actions and interacts with the world. Understanding the importance and challenges of learning agents that make decisions is of vital importance today, with more and more companies interested in interactive agents and intelligent decision-making. This course introduces you to the fundamentals of Reinforcement Learning. When you finish this course, you will:- Formalize problems as Markov Decision Processes - Understand basic exploration methods and the exploration/exploitation tradeoff- Understand value functions, as a general-purpose tool for optimal decision-making- Know how to implement dynamic programming as an efficient solution approach to an industrial control problemThis course teaches you the key concepts of Reinforcement Learning, underlying classic and modern algorithms in RL. After completing this course, you will be able to start using RL for real problems, where you have or can specify the MDP. This is the first course of the Reinforcement Learning Specialization.

Time: 18h

Instructor Details

Martha White

4.7 Rating
109 Reviews

Martha White is an Assistant Professor in the Department of Computing Sciences at the University of Alberta, Faculty of Science. Her research focus is on developing algorithms for agents continually learning on streams of data, with an emphasis on representation learning and reinforcement learning. Martha is a PI of AMII---the Alberta Machine Intelligence Institute and a director of RLAI---the Reinforcement Learning and Artificial Intelligence Lab at the University of Alberta. She enjoys soccer, the outdoors, cooking and especially reading sci-fi.

Reviews

4.7

109 total reviews

5 star 4 star 3 star 2 star 1 star

Write a Review

By Junfei S on 4-Oct-19

Good course in coherence with the book by Sutton and Barto (2018)! Better than reading the book alone.

By Harold L M M on 3-Oct-19

I really like this course. This course introduces the basic mathematical background needed in RL, as well as provided algorithms and hands-on programming practices in translating algorithms into actual code, which is a well-blended material for students to learn! The quizzes are very helpful as well, which helps me understand the concepts better. All the methods discussed here are quite practical and intuitive. Thanks Martha and Adam making this course fun!

By Ã©Â™ÂˆÃ¨Â¾Â‰ on 22-Oct-19

Short videos, with list of objectives at the beginning and recap and the end, and clear explanations in between. In my opinion, all teachers should watch these videos to get an example on how good courses are done.

By gregorius a on 22-Oct-19

This course is very benificial for the people who want to attempt to the area of reinforcement learning. People should regularly follow the book in parallel to video lectures to benefit from this course.

By Sonal K on 6-Oct-19

Great class! Learned a lot with two really fun and enthusiastic professors. Looking forward to the next one.

By Ayan M on 6-Oct-19

Great course! Good explanations, interesting assignments.

By Bence K on 10-Sep-19

Really nice and clear course, love it :)

By SHASHANK P on 9-Sep-19

The pattern of this course is amazing. Each video is short and has a specific objective that's clearly stated. This approach to teaching made tough topics look easy. Assignments and quizzes were doable. Amazing experience overall!

By Himansh C on 8-Sep-19

Great!

By Kiran B on 7-Sep-19

learned a lot, thanks !

By Kun C H on 29-Oct-19

Explica las cosas muy por encima, no va al detalle, las prÃƒÂ¡cticas un pelÃƒÂn difÃƒÂcil para gente que empieza.

By Shashidhara K on 13-Nov-19

I really sorry for giving 4 star, my only reason for giving 4 star is so you can read this review. Please include some exercise on calculating the equations by hand, with solutions(this is the only reason for 4 star). Thank you for the courseCourse deserves 5 stars.(pardon my 4 stars, sorry)

Visit Course Write a Review

Video Duration: 18h
Price: Free 0 Track Price
Provider: Coursera
University: IBM
Language: English
Certificate: Yes

Coursera Coupon Price Tracker

Email Address* Email me if the price is less than:

For any issues or feature requests please email CourseDuck's Co-Founder at michaelk@courseduck.com