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.
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!
By Muhammad U S•
Highly recommended for the beginners. If you are new to RL then this course is the best along with Sutton and Barto Book.
there is so many great fundamental stuff here, with deep theoric background, but it lacks some practical approach
By Christopher B C•
I thought the lectures were informative, but the pacing could have been a bit faster to get through more content.
By Rafael V M•
Excellent course, with several practical examples of the theory being explained. I found week 3 a little dense.
By Balsher S•
Week 3 should be improved a bit. It is a bit confusing to understand. Btw Great course. Keep the good work up.
By Sharmili S•
Quizzes and assignments are a bit challenging. It might be easier if questions are better elucidated.
By Arthur B•
Great course, yet a bit superficial. If you want to understand details, you have grind on your own.
By Daxkumar J•
this is a basic course of the RL and its very great to learn with University Alberta.
By Anirudh B•
Needs more coding implementation according to me. But overall theory was good.
By Zia M U D•
Tutors are fantastic, but should also focus on programming not just on theory.
By Mohamed H•
I think it will be perfect if the board and pen are used to drive equations.
By Maxim V•
Good content, but most of it is in the textbook, not so much in the videos.
By Sri R R•
The course was cool but needed some more programming assignments.
By Francisco R•
Excellent in terms of learning the foundations of RL.
By Jeroen v H•
Quite theoretical. But a good base of the concepts.
By Husam D•
I wished there were more coding assignments
By Shahram E•
By Mark R•
By Arpan M•
By Youval D•
Good examples can simplify things greatly. there where several places where an extra step would add value. Some lessons, such as the problem with the trucks could go a little deeper. Assignment grading system is buggy. I spend hours (that I do not have) because I used "transition" as a variable. After I figured this out, I was no longer able to know if other error is due to some other things the Notebook does not like or if there are actual errors. I also posted some questions but never got any response to any of them.
By Chandan R S•
Not much satisfied with the course structure...
To successfully understand and complete this course, you constantly need to refer the reference book.
Most of the students are referring to online courses so that they can learn more efficiently than reading,
any casual book reader can easily complete this course but for the person who like to learn from videos rather than book reading (like me), it was not so great experience.
By Rafael C P•
The content is there and it is good, but teachers lack good teaching skills and lessons feel rushed (Ng lectures come to mind as positive examples of good practices). Also, lessons aren't self-contained, as you need to read the book if you want to get good grades on the tests. I was looking for a smoother experience than the book, not to be told to read the book, which I can do without a course.
By Saeid G•
The good thing about this course is that it is based on the bible of reinforcement learning and it is thoughts by the experts in the field. However, the pace of the teaching is extremely fast and it is quite hard to keep with the pace even for someone with some background in the RL.
By Iuri P B•
It needs more explanation about the fundamentals, examples and sections that demonstrate how each, for instance, Policy Iteration and Value Iteration differ. Despite that, the course is really good and I would recommend for a friend.