6 июля 2020 г.
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.
7 апр. 2020 г.
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!
автор: Inge J•
2 сент. 2021 г.
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.
автор: George M•
5 мар. 2021 г.
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.
автор: Dmitry N•
24 окт. 2020 г.
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!
автор: Stelios S•
11 мая 2020 г.
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.
автор: Ali N•
1 апр. 2020 г.
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.
автор: Alejandro A Z•
20 июля 2020 г.
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!
автор: Иванов К С•
29 авг. 2019 г.
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.
автор: Nicolas T•
26 апр. 2020 г.
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!
автор: Anton P•
14 дек. 2019 г.
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.
автор: DANTE K•
28 дек. 2020 г.
Teachers were very clear and so was the book. The only thing I feel could be improved is adding some coding exercises on Week 2 and 3 (there's only one at Week 1 and one at Week 4, with a Peer Reviewed assignment on Week 2 which was fun, but didn't feel as useful as coding exercises)
автор: Sandesh J•
1 июня 2020 г.
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.
автор: Sara S•
28 дек. 2020 г.
Excellent Course. Although it was only 4 weeks course, I learned more than reading an entirely dynamic programming book which might take more than 3 months for me. It was a well-presented course and I suggest this course to the ones that want to learn about Dynamic programming
автор: Giulio C•
25 июня 2020 г.
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.
20 апр. 2020 г.
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.
автор: Majd W•
24 окт. 2019 г.
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.
автор: Juan C E•
9 февр. 2020 г.
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!!!
автор: Rohit P•
25 июля 2020 г.
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.
автор: Tolga K•
15 окт. 2020 г.
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.
автор: Yover M C C•
1 мар. 2020 г.
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 :).
автор: Le Q A•
2 авг. 2020 г.
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.
автор: Evgeny S•
18 апр. 2020 г.
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.
автор: Ayan S•
18 мар. 2021 г.
The course videos are exceptionally brilliant. It was my first course on reinforcement learning and the instructors did a great job in making this topic look super easy and intuitive. Looking forward to the next courses of the same specialization.
16 февр. 2020 г.
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
автор: Dan N•
22 окт. 2021 г.
Very good integration with the RL Book and step by step video presentations. Coding assignments well structured, however I would have liked to have more such assignments. All in all, very well though and structured course in RL fundamentals.
22 июля 2020 г.
The most professionally presented course I have done on Coursera! Instructors explain well, the provided literature is on point and the assignments had a good mix of being doable and challenging. Probably the best course I have taken so far.