Jul 07, 2020
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.
Apr 08, 2020
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 David R•
Dec 03, 2019
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.
Nov 20, 2019
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.
創建者 Jesse W•
May 10, 2020
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.
創建者 MOUAFEK A•
Apr 13, 2020
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!
創建者 LUIS M G M•
Oct 25, 2019
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!!!
創建者 Zhuang J•
Mar 24, 2020
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!
創建者 Shashank S•
Apr 13, 2020
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.
創建者 Dmitry N•
Oct 24, 2020
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!
創建者 Stelios S•
May 11, 2020
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.
創建者 Ali N•
Apr 01, 2020
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.
創建者 Alejandro A Z•
Jul 20, 2020
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!
創建者 Иванов К С•
Aug 29, 2019
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.
創建者 Nicolas T•
Apr 26, 2020
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!
創建者 Anton P•
Dec 15, 2019
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.
創建者 Sandesh J•
Jun 01, 2020
One of the best available courses on Reinforcement Learning. The instructors have explained all the underlying topics elegantly. Good blend of theory and numerical in assignments and programming problems. Moreover, the assignments have covered different perspectives on these topics.
創建者 Giulio C•
Jun 25, 2020
The book, on which this course is based, is a bible for reinforcement learning. Anyway, it could be hard to understand. The lectures of the course eliminate all doubts and consolidate all the concepts, ensuring a complete comprehension on the subject.
Apr 20, 2020
Great starting point for learning Reinforcement Learning. Anyone who is interested in the state-of-the-art RL techniques should take this course first, or they will have hard time getting through the more applied and sophisticated concepts found in the tech blogs or papers.
創建者 Majd W•
Oct 24, 2019
The thing that makes this course outstand among other Coursera courses is that it is based on a book. That gives you more information if you need it.
One problem that I guess will be solved in the future is that there is a bug in the Programming Assignment submission code.
創建者 Juan C E•
Feb 09, 2020
Excellent course. Excellent teachers. I love the introduction sections, in which you're presented what you'll learn in each video, and the summary section. The animated slides are also very professional. Very thorough coverage of the RL book. Congratulations!!!
創建者 Rohit P•
Jul 25, 2020
Some supplementary video recommendations and a little more interactive help with the Python assignments would make it more fun. Had to struggle with the programming assignments a little bit. More hands on assignments will help drive home the concepts better.
創建者 Tolga K•
Oct 15, 2020
Great course, great notebooks and great instructors, but nevertheless the reading parts of the course is most important part I think. Because if you do your reading well and really understand the material then course is just repeating over what you learn.
創建者 Yover M C C•
Mar 02, 2020
Excelente curso, aprendí los conceptos de aprendizaje por refuerzo con gran base teórica, el material del curso es muy bueno y la calidad de las lecturas es de excelente nivel. Muy recomendado, ahora a aprender más y a desarrollar sistemas inteligentes :).
創建者 Le Q A•
Aug 02, 2020
Excellent introduction. The reading materials are good, the videos make the ideas even clearer and the exercises help us get a taste of how the theory could be applied. I would recommend this course to anyone wanting to start on Reinforcement Learning.
創建者 Evgeny S•
Apr 18, 2020
I enjoyed the course. I would have preferred a bit more in-depth look at the algorithms and technical details, but, on the other hand, it was also interesting to go and figure out these contraction mapping arguments on your own. Overall, very good.
Feb 16, 2020
I had learned a clear understanding of terminology and the formulas of value function, action-value function, optimal value function, Bellman's equation, policy evaluation and iteration. It's a must go through course for Reinforcement Learning