After 4 courses in the stack, this one is the worst. My tip would be to look on youtube for a tutorial of the topic at hand and skip the UoM lecture.

lectures didnt cover material in assignments specifically week 4. lead to a lot of supplementary research and headache.

Too simple. Few information and content, and extremely simple (though with a lot of problems) assignments.

The difficulty of the assignments is in no way related to the simpleness of the lectures.

The NLTK library was not explained properly. No code explanation was provided.

Teacher does not explain well and lectures are not detailed.

Horrible assignment and horribl week 3 and 4. Please avoid!

Este curso no vale para nada, por favor no lo hagais!!!

Only useful for coarse understanding of the topic.

poorly prepared lectures, assignment instructions

tired of auto grader,...and prof not interested

totally can't understand the Indian accent.

the worst ever I took here in Coursera

worst course in the series by far.

Horrible, I lost motivation

I was not satisfied

broken assignments

Obsolete course

Horrible!

This class was fantastic. It was an order of magnitude times better than the previous course, 'Applied Machine Learning,' by Kevyn Collins-Thompson. Professor V. G. Vinod Vydiswaran started most lectures with a purpose and an alluring example. He spent a good amount of time building intuition behind the algorithms and techniques involved, and saved most of the coding for challenging and satisfying homework assignments--all qualities that the previous course did not have.

Finally, professor V. G. Vinod Vydiswaran was simply energetic about teaching. I didn't have to change playrate to > 1.2x. I genuinely enjoyed his teaching style.

This course has restored my faith in the 'Applied Data Science with Python' specialization by University of Michigan and I am confident in my ability solve text classification problems in Python. Highly recommended, along with the first two courses in this specialization.

I never knew, that the data that is present over the internet can provide such fascinating details, from which we can infer a lot. The teaching methodology of Professor Vinod where he introduces to the very basic concepts of this course, and then slowly and steadily moves to some of the core concepts of NLP is really fantastic. This course gives you all the key ingredients you need to create advanced NLP projects using python programming language.

Very good overview of the NLP tasks. The assignments were again really challenging and required a lot of navigating the documentation and forums. The autograder is really frustrating sometimes though especially when it can't upload your file and you miss that part and change your correct code. Again, the assignments are really difficult without help from the forums but it was worth it.

Great course! The assignments were at times hard to understand. Thanks to the wonderful support from the fellow students and mentors in the discussion forums, you will get most of the clarifications. Would recommend completing first 3 courses of this specialization before this one. There are a plenty of new concepts and new libraries introduced in this course.

I have been really interested in text mining for his wide applications. This course is very nice, it gives all the bases to deal with text mining problems! However, there could have been a Jupyther Notebook to put in applications the bases with Python about Topic Modeling in order to be more confortable for the Assignement 4.

This is a very helpful courses for text mining. It starts with cleaning data and then gradually build up the skills to classify and group texts. I love all the case studies. The assistant walks me through the tasks using the tools and methodologies mentioned in the lectures. It also helps to solve the assignments.