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Learner Reviews & Feedback for Applied Text Mining in Python by University of Michigan

3,478 ratings
668 reviews

About the Course

This course will introduce the learner to text mining and text manipulation basics. The course begins with an understanding of how text is handled by python, the structure of text both to the machine and to humans, and an overview of the nltk framework for manipulating text. The second week focuses on common manipulation needs, including regular expressions (searching for text), cleaning text, and preparing text for use by machine learning processes. The third week will apply basic natural language processing methods to text, and demonstrate how text classification is accomplished. The final week will explore more advanced methods for detecting the topics in documents and grouping them by similarity (topic modelling). This course should be taken after: Introduction to Data Science in Python, Applied Plotting, Charting & Data Representation in Python, and Applied Machine Learning in Python....

Top reviews

Aug 26, 2017

Quite challenging but also quite a sense of accomplishment when you finish the course. I learned a lot and think this was the course I preferred of the entire specialization. I highly recommend it!

Dec 4, 2020

Excellent course to get started with text mining and NLP with Python. The course goes over the most essential elements involved with dealing with free text. Definitely worth the time I spent on it.

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501 - 525 of 659 Reviews for Applied Text Mining in Python

By Jim S

Aug 24, 2017

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.

By eon t

May 7, 2020

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

By Sakina F

Apr 15, 2018

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.

By Oscar F R P

Aug 26, 2020

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

By Ashwani K

Apr 14, 2021

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.

By Reed R

Mar 7, 2018

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.

By James S

Feb 2, 2018

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.

By Tracy S

Mar 12, 2018

assignments are ok although with some unclear issues. however, i think the last week tutorials can be richer and more informational. i love the week1-3 tutorials.

By Kieran W

Feb 21, 2018

Overall good material. Not enough actual code examples at times, especially towards the end. The assignments weren't completely relevant and slightly buggy.

By Juan M

Apr 28, 2020

Seems sort of unupdated, lacking enough applications for the student to really get a grasp of the contents. Lectures should explain theory more thoroughly

By Saswati R

Jul 8, 2018

Some of the assignment problems, especially assignment 2 and 4, did not have clear instructions and hence were confusing. Otherwise, a good course.

By Rafael C

Aug 20, 2017

The course materials were interesting, but there were also a lot of issues with the autograder. Hopefully they will be fixed for the next sessions.

By Ali T

Dec 23, 2018

I learned some useful stuff in this course but I think it could be a little more deeper and teaching more behind theorems especially for week 4.

By Maxim P

Oct 12, 2018

Good Lectures. But much to less introduction by real examples. Especially in the last lecture you need to add a Notebook. As guidency and recap.

By Girija M

Jul 1, 2018

The subject is too vast to be covered in such small videos. Lot more details can be integrated. Great start for beginners to Text Mining though

By Mateusz M

Feb 6, 2019

Some of the topics where elaborated very briefly. There was not enough practical examples and instructor was no clear in what he was saying.

By Bernardo A

Aug 19, 2017

I liked the course, but it felt as a very raw overview, I think it could have been more challenging when it comes to the models explained.

By Shakshi S

Aug 4, 2020

The course assignments were somewhat difficult and also there should be more explanation of topics that were covered in this course.

By Alex W

Nov 14, 2019

Really poor instructions on week 4. Overall, was a great course that was a good intro to the text machine learning tools in Python.

By Lu E

Aug 30, 2018

I don't think the lecture is very clear. Although I have finished the homework, I still feel a little confused about the concepts.

By Panit A

Oct 22, 2017

Bad assignment. Grader not reliable. No control over the discussion board, many confusing comments mixed with good comments.

By Vishal S

Jul 16, 2018

Lectures are good but the assignment of week1 and week 4 is a little bit absurd and unclarified. Autograder is too slow.

By Nishal

Dec 4, 2019

The explanations weren't the best and pacing wasn't amazing, but some good ground covered and parts were interesting.

By Amir-Sina H

Apr 25, 2020

This is a good informative course, yet superficial at times. Specially when it comes to fourth weeks' assignments

By Thomas B

Apr 22, 2018

Some rather vague assignments instructions, some assignments require material only briefly mentioned in lectures