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!
創建者 Nathaniel W•
The instructions on how to translate equations to code could have either had examples in the presentations or in the jupyter notebooks. Overall an excellent course.
創建者 David S•
It will be good to include more detailed examples and more practice exercices in week 2 and 3. Also to repair the week 4 submission.
Although, It is a good course.
創建者 Muhammed A Ç•
Without reading the recommended book, course material would not be sufficient. Coding exercises quite good and also quizzes' are suitable for beginner level
創建者 Naresh T•
Good understanding of the fundamentals and aptly paced. The programming assignments were very good if there were more like that the course could get better
It brings general understanding. The main focus is reading the book. Assignments are about the introduction, help to understand, but they can be improved.
創建者 Romesh M P•
I really enjoyed the course, especially the guest segments (I got to know important people from that). Presenters did a good job but can be more relaxed.
創建者 Chokpisit K•
Very good introductory course for reinforcement learning. Good coding assignment, but could add more visual representation to understand the transition.
創建者 Marcello M•
Very good theoretical contents, pretty much in line with the textbook - practical coding parts are mostly exercises of conversion of equations into code
創建者 Mahmmoud M•
However, Missing the lectures of slide, the supported book is very good. The lectures are very simple and one can finish fast.
Thanks for teaching team.
創建者 Prakhar J•
The content was very well organized, but applications could have been better understood using more complex numerical algorithms and more assignments.
創建者 krishna c•
The guest lecture on truck fleet management was not great, the teacher tried to cover lot more material in a short time in the video then possible.
The fundamentals of Bandits and MDPs are well covered. A major plus is the way we are made to read the text book before attending the lectures.
創建者 Slav K•
A solid start with theoretical fundament. Assignment 2 was too cumbersome, lacking the description of actions encoded in the assignment.
創建者 Petru R•
More Python examples are needed throughout the lessons.
Not only at the final. No proper introduction to DL Python library is given.
創建者 NEHUL B•
I was hoping for a bit more practical application too, but this course does a solid job at teaching you the theory thoroughly.
創建者 Matthew C•
Auto-grading of programming exercises did not work that well, but other than that, it was very instructive and well presented.
創建者 Mark C•
The course is mostly a repeat of the text book. Fortunately the text book is free. Regardless, the material is interesting.
創建者 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.
創建者 Matthew W•
pretty good course for RL basics, not as in depth as the book and programming assignments were too easy, but good intro
創建者 parham M•
there is so many great fundamental stuff here, with deep theoric background, but it lacks some practical approach
創建者 Christopher C•
I thought the lectures were informative, but the pacing could have been a bit faster to get through more content.
創建者 Rafael V M•
Excellent course, with several practical examples of the theory being explained. I found week 3 a little dense.
創建者 Balsher S•
Week 3 should be improved a bit. It is a bit confusing to understand. Btw Great course. Keep the good work up.
創建者 sharmili s•
Quizzes and assignments are a bit challenging. It might be easier if questions are better elucidated.
Great course, yet a bit superficial. If you want to understand details, you have grind on your own.