Chevron Left
Zurück zu Practical Reinforcement Learning

Practical Reinforcement Learning, National Research University Higher School of Economics

201 Bewertungen
54 Bewertungen

Über diesen Kurs

Welcome to the Reinforcement Learning course. Here you will find out about: - foundations of RL methods: value/policy iteration, q-learning, policy gradient, etc. --- with math & batteries included - using deep neural networks for RL tasks --- also known as "the hype train" - state of the art RL algorithms --- and how to apply duct tape to them for practical problems. - and, of course, teaching your neural network to play games --- because that's what everyone thinks RL is about. We'll also use it for seq2seq and contextual bandits. Jump in. It's gonna be fun!...


von FZ

Feb 14, 2019

A great course with very practical assignments to help you learn how to implement RL algorithms. But it also has some stupid quiz questions which makes you feel confusing.

von VO

Mar 17, 2019

Well Prepared and taught course.. Will highly recommend as the primer for reinforcement learning

Filtern nach:

54 Bewertungen

von Dmitry Ivanov

May 23, 2019

Very reinforcement, much learning

von Mikhail Vilgelm

May 23, 2019

The material covered in this course is very comprehensive, up-to-date, and broad. It goes far beyond typical RL courses/tutorials. BUT, at the moment the course is extremely raw:

1) For larger/longer assignment, it is impossible to work with coursera notebooks (keep disconnecting); It takes lost of efforts to set-up own environment (and you shouldn't really count on discussion forum for help).

2) The assignments have bugs / broken links and other issues.

3) Finally, I believe the main issue is that there is basically zero support from the course personnel/tutors. It looks like the course was just abandoned by their creators and they don't care about it anymore. Very sad, since the material is quite exciting and deep, and the course has lots of potential.

All in all: 5 stars for the content, 0 stars for the organization = rounding down to 2 overall.

von Hamed Niakan

Apr 23, 2019

I would give it -5 star if it was possible. The course material is so vague but still understandable if you sleep on them 10 times more than watching it. Maybe Andrew Ng courses or Python Course or Advanced ML course on google cloud (GCD ) spoiled me However statistically and self-judgement , this is not the case.

The instructor talking super fast and not understandable that could beat any translator machine I bet. What s more, the instructor talking about things which are not consistent with slides and also sometimes he does not explain some formulas or modelings.

The assignments are full of grammatical errors and they are super confusing. Very simple but super confusing leads you to have the grader failed you.

But , The worst part is if you take this course you will be all on your own and no body help you out as TA . If you check the forum discussion you see how many people complaining and how many questions left with no answer. I took this course as granted , but this is my responsibility to give back my feed back to potential learners.

Note that this is my feeling from the first week of class , I hope my idea change later.

von Tingting Xu

Apr 22, 2019

I really like the lectures and homework, especially the coding assignments, which help me play games with RL and also improve understanding of the typical RL algorithms. Also, the discussion forum is very helpful and I can usually get out of stuck by following mentors' and other students' advice. Great thanks to Pavel Shvechikov and Alexander Panin for making such a useful course available!


Apr 07, 2019

Interesting topic, however several things are not acceptable for a paid course:

+ Some assignments are a mess, it's crazy hard to get the environments working right, very little instructions and explanations

+ Assignment graders are broken and require you to fix them manually

+ No consistency between the notations of the different lecturers

+ Slides from videos are not provided (seriously ?!)

Overall, the course does not look serious, a kind of alpha version.

von Felix Altenberger

Mar 18, 2019

The course itself is great, but the assignments are a bit chaotic (so make sure to bring a lot of patience and willingness to bugfix)

von Vaibhav Ojha

Mar 17, 2019

Well Prepared and taught course.. Will highly recommend as the primer for reinforcement learning

von Antony Lawler

Mar 12, 2019

Course not ready and has installation prerequisites. Seems to use a libraries (Docker, Env).

I waste too much of my time trying to install libraries and dependencies for online courses, most of which become obsolete within a year or two.

Additionally, the logic embedded within the library is often the thing I want to learn, and abstracting it only teaches me about the bugs and shortcomings of that library.

von Xiaoahe Xue

Feb 20, 2019

The course is well organized. Reference and extra learning items is helpful to enhance the knowledge.

BUT! There are so many small bugs in the assignments that it really takes time to fix and make the course hard to get passed.

von Ashish Jagadish

Feb 19, 2019

Horrible graders starting from week 3. A lot of time wasted in fixing grader issues which is course provider's primary job. This is a paid course for goodness sake. No proper communication by course's staff/mentors even in the discussion forums.