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Practical Reinforcement Learning, National Research University Higher School of Economics

4.2
154 ratings
45 reviews

About this Course

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!...

Top reviews

By 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.

By AH

Aug 17, 2018

Learned a lot. The pace is quick and the assignment is challenging sometimes

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46 Reviews

By Hany Abdelrahman

Feb 16, 2019

The course gives a good intro to reniforcement learning. I liked the fact the assignments here are shorter compared to other coursers. However, the quality of preparation of the material is very low. In many cases there are problems with the code and you cannot submit from coursera. I had to download the docker container locally and fix the bugs in order to submit. Quizes are not very nicely prepared and mathematical notation not very clear. I think I struggled a lot to get some of the quizes finished as the accepted score is quite high and some questions require multiple answers and you have to get them all right in order to get a score. I think the authors need to spend more time refining the quizes as well as the assignments

By Fan Zhou

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.

By Shahram Najam Syed

Feb 11, 2019

Overall a good course, But there are many bugs and errors in the programming portion of the course.

By Hamed Niakan

Feb 09, 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 with some Russian accent that could beat any translator machine I bet. What s more, the instructor some quite of time, 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.

By Ashish Jagadish

Feb 07, 2019

Horrible graders. Especially week 3's Q-learning is just a pain in the neck. Issues fixed only in the course's github page and these fixes are not reflected in coursera. A lot of time was wasted in fixing the grader's issues on coursera before realizing that the fixes were made available on github. No proper communication by course's staff/mentors even in the discussion forums.

By Roman Puttkammer

Feb 05, 2019

Four stars only because the notebooks/excercises don't work well. Aside of that, I learned a lot in this class. Thank you!!

By Milos Vlainic

Jan 30, 2019

This is my fourth AML course, and for now I would say it is the best one. It connects lectures and practice in the best way. On the other hand, there are mistakes all around, as it is beta-version. In my opinion, it is not fair to put the beta-version course into paid specialization.

By Anmol Gupta

Jan 30, 2019

The content was tough but the efforts were appreciable even if there were some hiccups along the way. The best part of the course was the plethora of information you get, don't forget to check out the references at the end of notebooks ;)

By 林佳佑

Jan 26, 2019

this course is helpful to learning Reinforce learning, but with some ambiguous context need a lot time to understand,

By Meytal Lempel

Jan 16, 2019

Great course. Thank you!