I don't feel like I learned very much; even a month later, I've almost entirely forgotten what we covered. The homeworks were confusing and often poorly worded, and from what I saw from the forums, I wasn't the only one who was left baffled.

The videos and content were great but the projects need more specificity. There's a lot of ambiguity around what the projects are asking for which takes away from the quality of the course. For examples, please visit the discussion forums.

This course was just too theoretical. There were just too many lectures on the English language and nothing really practical. I learned nothing that I can actually use. There were hardly any useful text mining techniques that I learned.

The lectures are pretty fast-paced, and the assignments expect you to do things that are not well covered in the lecture. You need to learn a lot by yourself to learn anything from the lecture. Besides, autograding is a disaster.

You do more work learning on your own to be able to do the projects and quizes then is given in the lectures. These University of Michigan classes aren't very balanced in terms of lectures, reading, and difficulty of projects.

Great teaching material and clear explanations. I learnt a lot.

Nevertheless the assignments auto-grading tool is awful.

I spent more time looking for the necessary hacks to pass the assignments than working on text mining.

Apart from the last week, where the videos does not explain anything related to the assignment, the way the exercises are worded is confusing and you need to look for tutorial about how to use the lda model, it was fine.

What is taught in the lessons and what is asked in the assignments have nothing to do with it. Assignments are too difficult. You can try if you want to challenge, but if you're just learning, I don't recommend it.

The content of the video and the assignment needs to be updated. Some of the questions in the assignment were not clear and autograder can be a pain. The topics are also not too coherent from weeks to weeks.

The assignment is very easy compare to the previous three courses, just need to apply some library and done. The syllabus is poorly designed, especially for the last two weeks. Overall, don't recommend.

Autograder bugs make for a frustrating time completing the assignments. Independent research and self-guided learning will come in handy for this course as the lectures (mostly) are uninformative.

A nice course overall but maybe not the best in the specilisation.

It may be me non understanding deeply the content but I found it a bit more mystical rather than quickly see concrete applications

A reasonable course for a "first" look at natural language processing, but, you will definitely need complimentary resources for grasping NLTK concepts. Overall a reasonable introductory course.

Too much time required to review discussion threads to understand or fix problems with the coding assignments. Lectures provided little substantive assistance in handling the coding problems.

There are too many issues with the assignments / the autograder in this course. Also, I haven't enjoyed the presentation of the content as much as in the other courses of this specialization.

Interesting subject, but compared to other Applied Python courses in the same track it felt more hand-wavy. Would have been interested in understanding more about details. Still good though

The course would be significantly improved if there were more hands-on demos during the lectures. Lectures are very high-level and aren't terribly useful when trying to do the lab exercises.

I faced difficulty to complete 4th week Assignment-04. There should be lab-worked in week-4. It will help to complete the assignment with proper understanding. Apart from that course is fine

Course content was informative and would benefit greatly from more depth. Some of the automated grading solutions are lacking/buggy. Excellent forum participation was key to success.

ambiguous, not very clear.

especially for the last course, the task could be difficult for novice

the course didn't present detailed explain for the code and sort of hard to follow

Very very long videos. Makes a person zone out. The videos need to be smaller in length as they become very hard to complete. However, the content is good and easy to understand.

Videos are too long and the lectures sometimes go too fast and shallow to grip on information for the assingments, though those can be very manageble consulting stackoverflow

The previous three courses has really made my expectation quite high. This course was fine, however a more details of programming examples and tutorials were needed.

Overall a good course and a nice introduction to Text Mining but issues with the autograder and some unclear instructions can make the assignments a little painful.

Some good stuff here, but really drops in quality toward the end and became a real slog to finish. Shame, since the rest of the specialization has been outstanding.