This course doesn't cover all concept of Sutton book. like n-step TD (chapter7) or some Planning and Learning with Tabular Methods (8-5, 8-6, 8-7, 8-8, 8-9, 8-10, 8-11), but what they teach you and cover are so practical, complete and clear.

Great course!!! Even better than the 1st one. I tried to read the book before taking the course, and some algorithmics have not been clear to me until I saw the videos (DynaQ, DynaQ+). Same wrt some key concepts (on vs off policy learning).

Course is not easy, videos presentation is a bit dull - but the material is cool and interesting, and the additional quizzes, videos and especially notebooks make it a great course - you learn a lot and see progress. Highly recommended.

This course required more work than the 1st in the series, (may be i took it lightly as the first was not that difficult). Request : Please include some worked examples (calculations) or include in graded/ungraded quiz, will be nice.

Phenomenal walk-through over Sutton & Barto's book. The programming exercises really help to dive deeper into the details of each algorithm, visualize their behavior and get dirty with the intricacies of the implementations.

Awesome! It is a pitty n-steps and eligibility traces were not included - felt like a huge gap. All the future chapters have a reference to the n-steps, and your understanding won't be complete unless you learn that as well.

Really great resource to follow along the RL Book. IMP Suggestion: Do not skip the reading assignments, they are really helpful and following the videos and assignments becomes easy.

Great course! The notebooks are a perfect level of difficulty for someone learning RL for the first time. Thanks Martha and Adam for all your work on this!! Great content!!

The course is intermediate in difficulty. But it explains the concept very clearly for me to understand difference between different sample based learning methods.

Well done. Follows Reinforcement Learning (Sutton/Barto) closely and explains topics well. Graded notebooks are invaluable in understanding the material well.

Excellent course and instructors! I'm very excited about this specialization. They are able to explain hard concepts from the book in an easy way.

Good balance of theory and programming assignments. I really like the weekly bonus videos with professors and developers. Recommend to everyone.

One of most accurate, precise and well explained courses I have ever had with Coursera. Congratulations for teachers and course creators.

An excellent course!!!! This is the best course I have ever taken on Coursera! Thanks a lot to two supervisors and teaching assistants!

I think it was one of the best courses to cover this topic. Clear and crisp presentations. Great programming assignments as well!!

Excelent course, I would love to do some other exercises out of the grid world but in general the content is good and interesting.

Very well prepared and interesting course! I will seek more for sure in the future! Thank you so much for offering this course!

I am really enjoying to learn reinforcement learning. The instructors are really good at explanation. Going for next course B)

This course is well explained, easy to follow and made me understand much better the tabular RL methods. I liked it very much.

This second instalment in the reinforcement learning journey is amazing. Although you can get stuck sometimes in some places.

I like the teaching style the emphasis on understanding and the fruitful combination with the textbook. Highly recommended!

Excellent course companion to the textbook, clarifies many of the vague topics and gives good tests to ensure understanding

Again, the course is excellent. The assignments are even better than Course 1. A really great course worth to take!

It is a wonderful and meanningful course, which can teach us the knowledge of Q-learning, expected Sarsa and so on.

Although I have learned q learning and td, this course still give me a lot of new feeling and understanding on it.