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!
por Nils S•
Very good an enjoyable course. It seemed like the explanations dwelled on the easier parts and skipped the parts that I would like to have seen in concrete numbers.
por 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.
por 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.
por 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
por 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.
por 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.
por Jo K•
Very good introductory course for reinforcement learning. Good coding assignment, but could add more visual representation to understand the transition.
por 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
por 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.
por Prakhar J•
The content was very well organized, but applications could have been better understood using more complex numerical algorithms and more assignments.
por 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.
por Slav K•
A solid start with theoretical fundament. Assignment 2 was too cumbersome, lacking the description of actions encoded in the assignment.
por Petru R•
More Python examples are needed throughout the lessons.
Not only at the final. No proper introduction to DL Python library is given.
por 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.
por Matthew C•
Auto-grading of programming exercises did not work that well, but other than that, it was very instructive and well presented.
por 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.
por Matthew W•
pretty good course for RL basics, not as in depth as the book and programming assignments were too easy, but good intro
por parham M•
there is so many great fundamental stuff here, with deep theoric background, but it lacks some practical approach
por Christopher B C•
I thought the lectures were informative, but the pacing could have been a bit faster to get through more content.
por Rafael V M•
Excellent course, with several practical examples of the theory being explained. I found week 3 a little dense.
por Balsher S•
Week 3 should be improved a bit. It is a bit confusing to understand. Btw Great course. Keep the good work up.
por 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.