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

4.8
stars
1,571 ratings
397 reviews

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

AT

Jul 07, 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.

NH

Apr 08, 2020

This course is one of the best I've learned so far in coursera. The explanations are clear and concise enough. It took a while for me to understand Bellman equation but when I did, it felt amazing!

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26 - 50 of 394 Reviews for Fundamentals of Reinforcement Learning

By K. S

Sep 22, 2019

Some of the sections seemed a bit rushed up. While the book provided a good source to clarify, I would prefer a slightly slower pace with emphasis on understanding during the video presentation. However, I have learnt significantly on reinforcement learning during the course. Thanks to the instructors who are highly accomplished, and have taken the time to create this video course.

By satheeshkumar v

Sep 12, 2019

What ever the content taught was really really good. but still more hands-on algorithms such as Monte Carlo would have been even better. overall worth studying the course

By Akshay P

Oct 23, 2019

Good overall. Need to work with your assignments and their submission procedure. Lectures should be more interactive than just going through slides.

By Waziha K

Jun 05, 2020

Course instructors should improve their teaching style by writing equations in hand and explaining point-by-point. There is no need to show their faces in the video while teaching. They sounded like 'radio' throughout the course.

By Ekaterina R

Feb 13, 2020

Not recommended

By Jonathan

May 01, 2020

Very well put together course. It does a good job of walking you through concepts in a way that's direct and accessible, while not dumbing things down. I had bought the Intro to RL textbook some months back but ran into problems getting its material to 'stick', but the ideas in chapters 1-4 are much more concrete now.

Assignments were reasonably difficult, but not overwhelmingly so. Homeworks are designed to make sure you understand key concepts moreso than being vigilantly 'rigorous' for their own sake. Emphasis of the class is making sure you understand fundamental concepts moreso than hacking your way into a working prototype of something.

While the class is designed to be easily digested, the material assumes a working knowledge of programming and mathematical formalism, so people without some background knowledge you might struggle to keep pace, even if the material is well designed.

Also, like others have mentioned.......this class follows the book pretty carefully. Don't expect anything to be covered that's not in the RL textbook the course is based off of. By the end of the class the book material will be more vivid and concrete in your mind, but you will not have branched into a direction not covered within it.

By John W

Sep 11, 2020

This course teaches you by having you read the textbook chapters (free pdf) followed by complementary videos that help you gain intuition. The quizzes focus on you truly understanding the material and are not easy. Quizzes plus two programming assignments help you actively learn rather than just passively reading or watching videos. I do wish the Discussion Forums kept a longer history of Q&A and had more responses from the instructors and mentors. For example, I had a question that someone else had already asked (so it wasn't an unusual question), but there was no response, and enough time had passed where the post became locked from any responses. So, I would really rate this course as 4.5 stars.

By Mukund C

Mar 08, 2020

Phenomenal Course. Very nicely done. Wish there were more active mentor engagement, however, since the student community for this course is not as large as at the time of this writing, so not much material to search through in the discussion forums. It will be good if some of the videos are consistent with the book - e.g. the notion of "control" is not in the text, but is introduced in Week4 for DP. Also, it'd be great to have some more lectures that dig deeper into "alternate" representation of Bellman equations (we are thrown this question in the quiz, but some working professionals, like myself can be quite rusty in English<=>Notation mindset, but that's a "very" small nitpick item.

By Maximiliano B

Jan 30, 2020

This course is excellent and it is a great introduction to reinforcement learning. I really liked that an electronic version of the book from Sutton and Barto is available for download as part of the course. However, it is fundamental to read the book in advance before watching the videos every week to have a better understanding of the concepts. Mr. and Mrs. White explain the content very well and it helped me a lot because the book is sometimes quite abstract if you are dealing with this subject for the first time. I definitely recommend this course to have a solid foundation in Reinforcement Learning and I am looking forward to start the next course of the specialization.

By Everest L

May 07, 2020

I've taken a few Coursera courses on machine learning/AI, and this is by far my favorite one. I love how the course is theoretically rigorous while still providing you with hands-on practice. Note: the short lecture videos don't contain all useful details, reading the (free) recommended textbook is a wise thing to do. Sometimes the quiz questions are drawn from the textbook, with slight modifications, and you'd be glad that you've worked through them prior.

No need to fret over reading every page of the textbook either, because recommended page ranges are given and they help.

By Mateo

Sep 17, 2019

I found the course really helpful. I have been learning RL for some time and it was hear that almost finally i can say that a lot of the concepts that were vague in my head became clearer. Also it made me look at the book of Sutton and Barto and found that it was a good experience. Maybe more examples and questions in between videos as in deeplearning.ai of Andrew NG could be good for keeping with the attention could be nice. Also maybe doing more programming exercises in between the ones we did in order to implement each step would be great. Thank you very much!!!!

By Douglas D R M

Jul 01, 2020

I believe that, as of now, this is the most educational and informative resource available online to learn the fundamentals of RL from scratch. the instructors use Sutton’s book as reference material (which is freely available online), guide you to details that no one would know are important when studying RL alone and prepare you to venture further into the area, with a solid foundation. I definitely recommend this as a starting point for anyone who wants to dig deep into RL.

By Saraj S

Aug 29, 2019

This is the best RL course I have ever attended. Even before starting this course I had brought the textbook (the one which course instructors also recommend) and was through the first 4 chapters. I understood most of the material but when I attended the class, everything was crystal clear. I hope instructors follow up and create the remaining courses as well. Please increase prgramming assignments in number as well. Thumbs up. Thanks for this course, very grateful.

By Kaylee Z

Oct 03, 2019

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 Mohamed S R I

Dec 22, 2019

The material in this course is of interest or me. It combines both theories and practical aspects of RL. The course follows the standard book in RL (Sutton & Barto Book).

One improvement may be needed is to add more "modern" examples and programming assignments/modules to explain the concepts. Also, it would be nice if the instructors can sometimes reflect on their own experiences with RL, rather than exactly following the book.

By Xiao Y

Aug 20, 2020

I have been interested in RL for a while and have watched many videos taught by other researchers, but this one provides something unique that helped me really get a deeper understanding of RL and gain confidence, such as the graded exercises, the quiz, I look forward to continuing this sequence of the RL specilization! Thank you so much for making the complex concepts accessible and make the quizzes and assignments!

By Jan Z

Aug 25, 2020

The course was very fun and informative. I really enjoyed the presentation style with clear outlines and summaries. The explanations were useful and easy to follow. Suggestions for improvements:

1) Provide a kindle version of the book, reading on screen is very tiring for eyes.

2) I think the programming exercises could use some work from SE perspective, as some of the code is not really pythonic.

By Karel V

Dec 16, 2019

The course is very well organised and professionally made. Although it follows the first four chapters of the Reinforcement Learning textbook, it provides a little bit different narrative and thus serves as a very nice complement to the textbook. Most importantly, interactive quizzes, programming exercises in Python and plenty of visualisations help to strengthen understanding of the concepts.

By 李谨杰

Apr 26, 2020

This course is the best course I have taken in Coursera! As a learner of RL in a non-English-speaking country, Sutton's book is too hard for me to accept a new idea very quickly. However, after watching the short videos in this course that summarize the core concepts explicitly, I can understand the contents of that book easily. Recommend for anyone who wants to study reinforcement learning!

By Christian C C

Aug 04, 2019

Exceptional course, the fundamental of RL explanations are excellent! I in particular I found it insightful the focus on thinking about examples in real-life that can be modeled as Markov Decision process. Additionally, great quizzes questions and assignments all helped in deepening my understanding of topics such as Dynamic Programing, Bellman Optimality, and Generalized Policy Iteration.

By Justin S

Aug 23, 2019

Excellent Course! The level of difficulty is perfect. It is difficult but not impossible if you do the readings in the textbook and understand the lectures. I strongly suggest reading the book before watching the lectures. This helped my understanding significantly. The material and assignments are very interesting and informative.

Highly recommend this course to anyone interested in RL.

By Bhargav D P

Jun 20, 2020

This course will give you the knowledge of most fundamental concepts of RL Like MDPs, Policy evaluation, policy improvement & value iteration algorithms. Even though you follow theory well, quiz and assignment will challenge your knowledge to think into bit more deeper level. frankly speaking, I took some quizzes three times and at the end I learned the concepts very well. :)

By La W N

Jul 01, 2020

So far so good. The course is really valuable. It'll be better if there are more explanations about mathematics used but there is discussion forums so not a big problem. It is ineffective in teaching the practicality, i.e, how real word problem can be related, what kind of problems can be solved by these methods. Overall, it is a great explanation about reinforcement learning.

By Joosung M

Jun 02, 2020

The content was very interesting, the instructors made things very clear that they were a great help in understanding what was really happening in the textbook.

I loved that this course provided a textbook with a lot of examples and case studies. I am willing to learn more about RL in the next set of courses.

Thank you so much for proving this wonderful specialization.

By Thomas G

Apr 01, 2020

Fundamentals of Reinforcement Learning is one of the best Online Courses I did on Coursera. I like that the course is based on a text book (Reinforcement Learning by Sutton), so you can really dig into the theory. Also the exercises are very helpful and ambitious which I like. I haven't found much advanced online courses which are so well explained like this one.