Practical Reinforcement Learning

Pros: It is a pioneer RL course in Coursera. Great exercise templates with interesting applications of RL algorithms. There are always references to good papers and new developments in RL. Good sense of humor in the lecture and templates. The discussion forum addresses the the bugs of the course. The course is challenging in the right level. Cons: The lectures are not in that level yet … they do not explain the important parts in detail. The lecturers should improve their public speaking and storytelling skills. The course subverts the sequence of the RL topics (cross entropy is the first method and the multi armed bandits setting is in the last week). This could be good, but ended up being confusing. The quizzes and exercises still contain many bugs. Overall: This is a good course, but it has the potential to be much better. If you want to challenge yourself and solve really interesting problems, take this course. You will probably have to watch David Silver’s lectures on YouTube and read some parts of Sutton and Barto’s book to understand the concepts. However, if you feel frustrated dealing with bugs in the exercises or answering quizzes that are confusing, do not take this course.

This course was theoretically fulfilling, however i felt that the teachers failed to explain core principles with ease and felt a connection break in between their accent, their lectures and the slides in the background

Great course. Thank you!

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 😉

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

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

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.

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

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.

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.

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.

Submission python code is very buggy. Instructors are hard to understand.

Some details are not explained as clear as it can be, maybe there can more reading material to bridge the knowledge gap between course syllabus and intermediate level ML experience. Nice work tho!

Overall very informative and well done course, I highly recommend it. The support in the discussion forums is the main area where it lacks. Sometimes the topics are hard to grasp, so it’s really a big help when there is good support in the forums.

Course was very challenging what is good! Did several courses that were too easy. Quizzes were sometimes difficult to pass because of the way the answers are evaluated (all answers have to be correct) and even after watching the video several times the answers were not obvious. Small things in the notebooks e.g. in mtc code was needed at a place but there was no comment saying that it is needed. In another notebook the wrong environment was loaded per default and had to be changed based on the notes given at the end of the page.

This is really a good course to deeply understand and apply the reinforcement learning. Thanks to instructers…

Very interesting topic and well taught. THX

Fantastic class if you don’t mind to overcome some code issues in the homework.

Challenging (unlike many other courses on Coursera, it does not baby you and does not seem to be targeting as high a pass rate as possible), but very very rewarding.

I’ve done about 14 courses on coursera and this was the worst. The teachers are so obsolete. They just rattle off a pre written text without any intonation. Instead of the videos it’s easier to just read a book on reinforcement learning. I still gave it two stars because the programming exercises were interesting and usefull.

I’m very happy to accomplish this course! Now I have a much clearer picture of RL methods. In order to pass this course you’ll require a good knowledge of python and some nonzero experience with tensorflow. Some tasks are really hard to pass, once I even had to install environment and run training on my home computer for several hours. I want to say thanks to course authors and a little suggestion: please add topic about curiosity in RL.

Excellent course

yes

Very practical lecture. I strongly recommend this lecture. Programming assignments are little difficult, but not impossible 🙂 Just do it!

Course is good. But too many grader issues. Accent is tough to understand sometimes. The concept is not built layer wise..Instead they dump it as a heap with tough jargon which had to broken down to be understood slowly by pausing..