Ratings and Reviews for Applied Text Mining in Python

the course is ok, should be more technical though.

Good course content, but no in-depth discussion of topics. Assignments are also very buggy.

Good introduction into the field of text mining, but very brief. I think the structure could do with some fine tuning as for example the extraction of features from text is left mostly untouched or is covered by the home work only. All in all I found it slightly less well structured than the previous parts in the series, but it was still very useful and helpful as a starting point.

Instructors did a poor job of preparing students for the assignments.

Content in the course is interesting and given the amount of data stored in text very valuable. However, I would encourage the staff to provide more coding examples. I would also suggest moving away from assignments and towards projects - (a) projects would likely force more comprehension instead of code shopping and (b) the autograder is terrible: I can't believe the amount of time I wasted because the autograder was not set up properly.

This was hard but worth it. However, it didn't have extensive coding examples, which made it pretty hard to apply techniques on assignment. It might be a good way to induce creative thinking but very painstaking for students. Be aware!

Great course, could improve the last week with more practical examples.

Very disappointing course. Probably cause I have learnt text mining from other specialization, does not feel this course is necessary to take. Assignment material are poorly prepared, waste some time when completing the assignment, which can be avoided.

Excellent course! Everything is understandable and interesting. I hope it'll help me in my future career. Thank you a lot!

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.