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Learner Reviews & Feedback for Fundamentals of Reinforcement Learning by University of Alberta

4.8
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2,737 ratings

About the Course

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 problem This 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....

Top reviews

AM

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This course is great for people who are just starting out. The programming assignments are really great and practically introduce you to the basic concepts of reinforcement learning.

MN

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The concepts may sound confusing in the beginning, but as you go forward you find it interesting and understanding. I suggest you completely read the reading assignments before watching the videos.

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126 - 150 of 657 Reviews for Fundamentals of Reinforcement Learning

By Sharath K

Jun 20, 2021

This is the best course I've found on RL. The lectures are to the point and both the lecturers are very good. The best part however is the graded assignments at the end of each week where we get to apply everything we learnt.

By LI C Y

May 2, 2022

This is not an easy cousre even to a computer degree graduate but it opens my eyes further on AI. I am understanding why RL is really quite different from ordinary supervised/unsupervied machine learning and neural networks.

By Nilesh A

Feb 22, 2022

Challenging and perfect introduction to reinforcement learning with a great blend of theory + quizzes + practical and discussions in between to engage. Thank you everyone for this course. Moving on to the next course.

By Juan P V H

Feb 28, 2021

Really good course.! The videos help to understand difficult concepts. The last assignment was challenging for me (I'm Ph.D. in electronics, not in computer science). In general a really good and recommended course.!

By Feng T

Nov 18, 2022

This course provides a good summary on the basics of Reinforcement learning. I really like the invite talks in this course as it provides some a different angle in understanding the materials and their applications.

By William R

Jun 6, 2022

The course was very good overall. The lectures are clear and succinct. I think the programming assignements need to be reworked a bit. I think the way the helper code is setup in the assignements is not so pythonic.

By Ismael E

Mar 29, 2021

Great course. I specifically recommend it as a completion to the reference book by R. Sutton. That course really helped me better understand some of the key concepts in the book. Looking forward to the next course.

By Andrew S

Aug 10, 2020

Amazing course. Amazing contents. The book is perfect and the lectures help clarify doubts that one may have from reading the book. With there were more programming assignments, but still it is a very good course.

By Guto L S

May 27, 2020

Very good course! It introduces basic concepts necessary to understand the basic reinforcement learning algorithms. The course is well structured, and the practical activities help a lot to fix the studied content.

By VBz

Oct 22, 2019

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 Anh N

May 30, 2020

The reading is a little bit challenging, but everything was explained very clearly with helpful examples in lecture videos. Absolutely recommend for someone who want to explore the field of Reinforcement Learning.

By Shahriyar R

Sep 22, 2019

Extremely useful course. Especially the format is very effective. First read the book, then listen the extra explanations and write Python code. Concepts are really clear for me now. Thanks for such amazing work.

By Joe S

Mar 27, 2023

Good reading material, good lectures, good practice quizzes and good labs. The material does a good job of combining the rigor of the Bellman equations with an intuition of what they mean and how they are used.

By Dani C

Jul 25, 2020

I was already familiar with a lot of the subjects in the course, but the way Martha and Adam explained everything really cemented all of the knowledge for me. Now instead of just familiarity I have real skills.

By Tristan S

Apr 7, 2020

Great course for learning fundamentals. My only complaint is that I don't quite feel comfortable implementing what I have learned with coding yet. Maybe as I progress in the specialization this will get better.

By Rafael B M

Aug 16, 2020

The course build up a solid ground for building more complex concepts of Reinforcement Learning, It's essential to master the core fundamentals of RL in order to seek more powerful and sophisticated methods.

By Nicolas S

Mar 11, 2020

Excellent course, with an excellent explaination of Markov Decision Process and Dynamic Programming by the 2 teachers. The quizzes and the final exercice are challenging and make you search in the text book.

By Dashiell S

Apr 2, 2021

Well designed, well taught course. I think I'd have liked it if there were more and tougher programming assignments as opposed to the quizzes, but this definitely provides an accessible introduction to RL.

By Jau-Jie Y

Jul 2, 2021

Very good explain, and included some real world example, like trunk assign.

The dynamic animation of grid world MDP calculation also was good, though I hope more slowly show the steps interval.

Thanks a lot

By Gökhan A

Oct 22, 2019

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 Lim G

Apr 15, 2020

This course is clear in its delivery. The examples were helpful in helping me grasp the concept. I understood the fundamentals of reinforcement learning and I am able to apply some basic element of it.

By Ahmet T

Jul 7, 2020

An excellent introduction to Reinforcement Learning, accompanied by a well-organized & informative handbook. I definitely recommend this course to have a strong foundation in Reinforcement Learning.

By Kaustubh S

Sep 2, 2019

All the concepts were well explained and this course was perhaps the best I have found for RL.

Great efforts have been put into making the course and It goes well in line with the suggested textbook.

By Mohammad N

Apr 12, 2024

The concepts may sound confusing in the beginning, but as you go forward you find it interesting and understanding. I suggest you completely read the reading assignments before watching the videos.

By Shi Y

Oct 4, 2019

许多次尝试看UCL或者Sutton的课都中途放弃,太难了。而这个课程让我很轻松的入门且了解了最基本的东西。这个课程最不同的在于,学习时要配合上Sutton的书,课程和书互为补充,有些课程没有讲清楚的地方书中有很多解释,而书中生涩难懂的地方课程又有很形象详细的解释。体验极佳。特别感谢课程助教即使的回复。哪怕是书中的句子的问题助教都给出很详细的解释,真的很久没在Coursera上过这么棒的课了。