So far so good. The course is really valuable. It'll be better if there are more explanations about mathematics used but there is discussion forums so not a big problem. It is ineffective in teaching the practicality, i.e, how real word problem can be related, what kind of problems can be solved by these methods. Overall, it is a great explanation about reinforcement learning.

The content was very interesting, the instructors made things very clear that they were a great help in understanding what was really happening in the textbook.

I loved that this course provided a textbook with a lot of examples and case studies. I am willing to learn more about RL in the next set of courses.

Thank you so much for proving this wonderful specialization.

Fundamentals of Reinforcement Learning is one of the best Online Courses I did on Coursera. I like that the course is based on a text book (Reinforcement Learning by Sutton), so you can really dig into the theory. Also the exercises are very helpful and ambitious which I like. I haven't found much advanced online courses which are so well explained like this one.

Great course. Theory-heavy, it follows the Sutton-Barto book chapter by chapter (up to Ch. 4. in this course), the quizzes are relatively hard, the programing assignments are fun and with the given number of hints they can be done in a reasonable amount of time. I really enjoyed this one and looking forward to the next course of this specialization.

RL is not an easy topic, but the instructors made sure to illustrate the concepts with a lot of examples and visualizations, making it much easier to digest than reading the textbook. Guest lectures were fascinating. Programming assignments in Jupyter notebooks are super helpful with a lot of step-by-step instructions. An excellent course overall.

Outstanding course. Instructors are great. The course alternates between important readings and well-crafted videos, quizzes and assignments. As you progress, concepts get tangible and you start figuring out possible applications. Do check out the required background knowledge. I've immediately enrolled in the second course of the specialization.

I really liked this course. I think it was challenging and high quality. I don't understand complaints about it following the book - I found the videos, quizzes and exercises insightful and thought provoking. And besides courses are meant to follow some material and not re-invent the wheel. Am really excited for the rest of the specialization.

The course was great. Very clearly explained, with meaningful examples and backup material, such as the recommended book.

My only comment will be on the case study given on the final programming assignment. The parking scenario was not very intuitive or clear for me. It took me quite a bit to understand what it was we were trying to optimize.

Excellent course. Covers all the basics at just the right challenge level, assuming you've had some Python programming experience and know a thing or two about probabilities and expectation values. They provide a PDF for a course textbook which is extremely well-written, and the videos are high-quality and complement the readings well.

This course was a great introduction to reinforcement learning. I found the material both accessible and applicable to a number of potential real-world problems. The combination of reading, video lectures, and example coding problems was an effective way to "reinforce" the course materials and build a solid foundational understanding.

After studying Classical Machine Learning and Deep Learning, and applying them in real-life cases with some startups and companies, some aspects of day to day problems did not seem to be fit while trying to use the previous methods, thus I dived into Reinforcement Learning looking for answers, and so far it's been very promising!

I started to read Sutton & Barto book this summer, and although I find it fantastic, some concepts were not 100% clear to me. This course has changed it dramatically. Now every concept is clear to me. This book is like reading a book with the support of very good explanations.

Let's go for the 2nd course in the specialitation!!!

You really need to understand fundamentals before kick start for any real world reinforcement learning problem. That's why this course is very essential. Plus it also provides programming tasks and multi-choice question sheet to deepen your understanding about theories. Great! Looking forward to move on for next series!

Really good course, and happily surprised and thankful it's based around Sutton and Barto textbook and with close links between instructors and those authors - I'd bought it a year ago with the best intentions of getting into RL, but needed something practical like this to help me get into it! Amazing work all involved

This course was a great first introduction to reinforcement learning! The course instructors make the material very accessible and the course follows the textbook very closely. I'd definitely recommend it to anyone trying to understand reinforcement learning and I personally plan to complete the entire specialization.

Excellent introduction to reinforcement learning. The two instructors are well spoken and the material is interesting. This course focuses mainly on the math/concepts rather than having a lot of programming. That being said, there are a few programming assignments which will help you to increase your understanding.

A very good introductory course. I agree that its content overlaps other courses on this platform. Still, the instructors never promised to create something completely different than those, so we should ignore that.

Video presenters should be a bit more relaxed to allow the audience to follow through more easily.

Sometimes it was hard to follow. In those cases re-reading the book helped. It is nice that in videos you, guys, have solved some of the exercises from the book. Also, it helped a lot to re-cap the material by re-doing the tests (and of course by reading a helpful notes, if the answer was incorrect). Thank you!

This is the BEST course I've taken from Coursera, period. The level of explanation, the usage of mathematically precise terminology, the walking through of the algorithms, the summaries were all top-notch. This course will be my reference when I forget something in the future. I can't thank the creators enough.

It was a very good course, I had read Sutton's book first. But I must say that after completing this course, I learned the concepts of the book well. Although the exercises were a bit tough, they covered the topics well and increased learning at a faster rate.

For anyone interested, I recommend this course.

It was really cool! Although I think there should be a forum where students could ask and answer questions. I got stuck for a silly mistake before delivering the last python notebook and could have used some help.

Still, I learnt an incredible amount of concepts that I didn't imagine were so important!

It's difficult to estimate this course because it's based on the book. I mean, 90% of materials i've seen on videos were on the book. That's very unusual, but effective. However, i've learned necessary information and python tasks were useful and interesting. I'll take the next course and will see.

Solid introduction to reinforcement learning. Provides great examples, and resources to help students understand the algorithms and math behind reinforcement learning. Also provides great programming assignments to help you understand how to implement such algorithms, with practical examples.

Great course! The idea of suggesting reading before the videos gives a huge boost to the depth of the class. This, with the "not-too-straightforward-quizzes", and the assignments, makes it a real deep class, from which I'll probably learn and retain more than most online courses. Good job!

It is a very well laid out and taught course. The instructors make the material accessible with a bit of a mathematics background, or a willingness to learn. I will be taking every machine learning course I can from AMII and the UofA if the rest of the courses are of the same quality.