Excellent course. You'll learn how to apply techniques like Neural Networks to Reinforcement Learning Agents. The assignments are very well designed, and they have the right difficulty so you can learn the most fundamental concepts of the course.

Very well made course. This helped me build Agents for our mobile board game! I'd like some more practical tips as well though, like how to make algorithms converge and things to try out. Other than that, I recommend this to every RL enthusiast.

Awesome course that complements both first courses on RL. Excellent chapter selection from the book that shows just the necessary and sufficient information to get a good idea of many of the concepts of function approximation. Very recommended.

I enjoyed the course because the content delivery was clear and concise. The hands-on assignment helped me better understand the concepts that were taught. I was able to draw connections and link between textbook and hands-on experience.

A very ambitious course where you have to invest a lot in reading the book but therefore you also learn a lot. I prefer more of those advanced courses here on Coursera.

The course is a very good complement to the book from Sutton.

Its got a great variety of very applicable examples, use cases, and assignments. May be tough if people don't quite understand how neural networks work, so I suggest having a basic understanding of NN for parts of this course.

Excellent course! The assignment could be improved by adding input checking in methods with one-hot encoding of state as input. Which I suffered when I forgot to use the one-hot encoding and spent much time debugging.

These series of courses provide one of the best materials for an introduction to reinforcement learning and optimal control. If you are motivated to learn and challenge yourself with RL, don't look elsewhere.

Thank you so much for this invaluable gift.!! I am a knowledge seeker in Reinforcement Learning and UOA is my dream place I am wishing to enter for my Ph.D. This is a good guide I received. Many thanks.!!!

Difficult but excellent and impressing. Human being is incredible creating such ideas. This course shows a way to the state when all such ingenious ideas will be created by self learning algorithms.

The course extends the foundations of Reinforcement Learning to function approximation, which allows the application of the previous learned method to tackle more complex and real world problems.

Well peaced and thoughtfully explained course. Highly recommended for anyone willing to set solid grounding in Reinforcement Learning. Thank you Coursera and Univ. of Alberta for the masterclass.

Surely a level-up from the previous courses. This course adds to and extends what has been learned in courses 1 & 2 to a greater sphere of real-world problems. Great job Prof. Adam and Martha!

Adam & Martha really make the walk through Sutton & Barto's book a real pleasure and easy to understand. The notebooks and the practice quizzes greatly help to consolidate the material.

I had been reading the book of Reinforcement Learning An Introduction by myself. This class helped me to finish the study with a great learning environment. Thank you, Martha and Adam!

I recommend this course for all students or professionals that would learn more and deeper about reinforcement learning. Thanks to all the team that participate to create this course.

Great Learning, the best part was the Actor-Critic algorithm for a small pendulum swing task all from stratch using RLGLue library. Love to learn how experimentation in RL works.

The course was really good one with quizzes to make us remember the important lesson items and well polished Assignments are given which i haven't seen before in coursera

Good course with a lot of technical information. I would add another assignment or make current ones a little bit more extensive, as there are many concepts to learn.

Prof Satinder Singh lecture of "Where the rewards come from in RL" is very suprised.

Thanks to Prof Martha White and Prof Adam White, for their lecture and management.

Super interesting, challenging but the videos are very helpful to complement the understanding of the Sutton and Barto RL book. Thanks the Univ. of Alberta team!

I found the course quite tough but really interesting. I would say that reading the book's chapters more than once is necessary to optimally grasp the concepts.

This is the third instalment in reinforcement learning.so far so good. yeah, you can get stuck some times but it is okay you can make it out.

I consider the professors explain in a feasible way the main concepts of RL hence communicate effectively and concise in the course videos.

This specialization is a gift to humanity. It should have been inscribed into the golden disc of the Voyager and shared with the aliens.