Jul 6, 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.
Apr 7, 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!
By Vaddadi S R•
Mar 10, 2021
The programming exercises are quite tough and difficult to code on our own. Concepts were explained nicely, however, lacks examples. Working out examples would have given an even better insight. Another video that could have proven useful is how to convert a real-world problem into an MDP.
By Thomas T•
Jan 26, 2022
Course is rather poorly structured. Some videos explain concepts better than others but come later in the courses. There's not enough of a summary of terms, and seems to follow the suggested book almost word for word. The course should use the book as supplementary not complimentary.
By Saeid G•
Dec 10, 2019
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•
Jul 3, 2020
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.
By Amr M•
Mar 14, 2021
The material needs to be easier and more intuitive. Last assignment shall have some additional steps to help the student to solve it. and also to involve him more
By Soran G•
Dec 9, 2019
The size of different variables has not been clearly spelled out so this makes the concept confusing and requires so much time to figure them out.
By Alessandro o•
May 14, 2020
It was quite difficult for me to follow. The concepts are explained very quickly and can be though. I found exercises very helpful though.
By MOHD F U•
Feb 12, 2020
Need a clear explanation of topics with a way to code as explained by Andrew NG in Neural networks and deep learning by deeplearning.ai
By Kun C H•
Oct 29, 2019
Explica las cosas muy por encima, no va al detalle, las prácticas un pelín difícil para gente que empieza.
By mehryar m•
Jul 16, 2021
It was quite comperhensive and intuitive one !
By KAUSHIKKUMAR K R•
Sep 27, 2020
I automatically transferred to Auditing mode.
By Vadim A•
Apr 14, 2020
More explanations to theory would be nice.
By Jeel V•
Jun 13, 2020
More details in teaching concepts
By Marju P•
Jul 30, 2021
The course was disappointing for two reasons: poor instruction and poor content. I was expecting a high quality course from Coursera, but was instead finding myself with instructors that simply read a textbook to you. The instructors did not provide any added value. They read the book, even used the exact same examples and slides as in the book. Moreover, this was done in a a boring monotone way. The instructors seemed frozen still, eyes glazed over (with boredom?) with the exception of their lips that moved as they read the slides. Good instruction includes giving more value than just reading a book: new and different examples, different explanations, or at least different wording, personal commentary, sharing own intuition, and linking material to the broader world, making connections between ideas. All of this was missing. Furthermore, the course is not inclusive. The few examples that were chosen were applications to chess and golf. In other words, activities of the privileged few. RL is highly relevant in our world where AI solutions are springing up in all areas of life. There is a wealth of examples that are relatable to a wide variety of people. Instead, by choosing golf and chess, the instructors are alienating the majority of their students. This is in stark contract to Coursera's own mission of expanding and promoting access to high quality education for ALL people regardless of their background (including socio-economic background). The course could be improved by adding content (commentary, explanations, examples, discussions) that has not appeared in the book. Relating this content in a student friendly manner (not monotonically reading slides). In short, the instructors should follow the basics of modern provably effective teaching practices.
By Simon S R•
Sep 1, 2020
They put a lot of effort into it the course, however, they choose for some reason not to share the slides with their students. The accompanying book may be the standard, but yet it does not summarize the content as the slides do.
The programming examples are to simple and to few.
A vast amount of the video contains 'what we are going to cover' and 'what we have have'. This would make sense, if there are longer videos, but not if there is just one or two minutes of content.
By Eli C•
Sep 15, 2020
the first and only other coursera course I took was mathematics of machine learning from imperial university of london. I found it challenging and educational, with fantastic presentation. it may serve as a good model to improve this course
By Amr K•
Jan 25, 2021
A Lot of theoretical math and Too few code I recommend to show this complex mathematical equetion in code also
By Jeon,Hyeon C•
Apr 6, 2021
등록 취소가 안되서 1점 드립니다.