Chevron Left
Back to Applied Text Mining in Python

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

4.3
stars
3,298 ratings
626 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

CC
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!

GK
May 3, 2019

Lectures are very good with a perfect explanation. More than lectures I liked the assignment questions. They are worth doing. You will get to know the basic foundation of text mining. :-)

Filter by:

51 - 75 of 617 Reviews for Applied Text Mining in Python

By Brian L

Oct 19, 2017

Great course! I have been doing some text mining in another tool, and I learned some useful things that I was able to put to use almost immediately ... now that I have the data science part in hand, I just need to figure out some Python details in order to format my output for my client.

By Davide T

Aug 18, 2017

Great teacher, great course. Topics are very interesting and well explained, assignments' difficult is just right. I'm sure they will put this review in some kind of sparse matrix in order to train a classifier and make previsions for future students...so it is a must-join course!

By Praveen R

Dec 10, 2019

I learnt about NLTK package and its capabilities. It was good to know how to build vocabulary and guess missing words and match sentences lemmatizing them. Good eye opener course. There is way much more to be learnt in this subject. This is just an introduction (a good one).

By Dipanjan G

Aug 16, 2020

Very Nicely taught course. Lots of example and week 1 case study was full of learning. But this course needs a bit of revamp as the transformer models such as BERT, Roberta and other self attention transformer models has completely changed the NLP landscape

By David R

May 17, 2018

When looking at the full course in coursera, I was thinking that would be the course which would interest me the least, but at it turned out, now I'm really interested in text mining, and I'm planning to read more publication to understand that field

By Binil K

Aug 15, 2017

This is a fantastic course though you might find some trouble with the grading part (Auto grading). This course will give you a good understanding about the various most useful techniques in text mining. Course is well structured and really helpful

By LENDRICK R

May 11, 2019

Well-taught course, I'd been struggling with regular expressions, thank you for simplifying the concept; additionally, you've opened my eyes to an entirely new world of data science for which I can think of an immediate productive application. :-)

By BrajKishore P

Jan 30, 2020

The overall course was well designed, all lectures were arranged in a proper sequence and all the slides and jupyter notebooks were good covering all the aspects, but I felt some difficulties in the 2nd week in POS tag, overall it was too good.

By Eunjae J

Aug 26, 2017

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!

By Varga I K

Mar 5, 2019

It was a great course about data mining. It covered the basics well. I would have liked maybe another week covering the topic distribution and it would be really nice if there were a notebook for every code shown in the videos.

By Athanasios S

May 25, 2018

Exceptional!

I was using up to now strictly regular expressions for text mining, and that was a headache.

This course opened a new whole world to me! I strongly recommend it to any one that wants to use ML to study texts

By Валерий Н Г

Aug 25, 2019

Great course! Even fighting with the grader didn't spoil the joy from learning new things)) Forum with useful comments of classmates is really a big deal. Thank you everyone who succeeded and shared their findings.

By Vinayak N

Oct 8, 2019

Well-structured, awesome pedagogy and challenging assignments. It has all the elements it takes to make a MOOC epic! Thanks UMich and Coursera for helping put this course together and allowing me to pursue it.

By Jitesh S

Apr 9, 2020

Assignments were very well designed and tested the understanding thoroughly. The lessons were crisp and the instructor had put in a really great effort in designing the overall layout.

Kudos to professor.

By Lucas G

Aug 16, 2017

Good Course! The expected format for the assignment answers is often a little bit too finicky, but with careful reading of the prompts, they are all doable, and the tasks themselves are fun and useful.

By Carl B

Sep 20, 2017

Excellent course! Video lectures are high quality, with realistic problems and applications. Exercises are reasonably challenging, and all quite fun to do! Strongly recommend this course

By Tony K

Jun 23, 2020

Everything was awesome, assignment 2 was my favorite in a long while in this specialization series. Week 4 was a little weak, and felt rushed. Overall, I enjoyed this course 4 of the 5.

By Maxwell S d C

May 26, 2020

The course is great, but I would suggest some contact with the issues and problems faced. Some parts of the exercises are advanced for those who have never had contact with the subject.

By Punam P

Apr 20, 2020

Nice experience..Thanks to Resp.Professor for clear the concepts so deeply and enhancing the knowledge in right path..Niceever and helpful course..Thanks to team & university..

By Manuel A

Sep 8, 2018

Just enough theory and an comprehensive guide through regex, nltk and some features from gensim (LDA). Assignmets are very challenging and some nice utilities are developed.

By Fernando M

Aug 15, 2020

It was a great course, I am really enjoying this specializtion. Even it is a great course, I think the previous in the specialization were better, maybe i like them more.

By Sonu C

Jul 5, 2018

Great course, very well balanced pace of learning. Adds good amount of working knowledge with NLP tools; definitely not covers everything but more than what I expected.

By Chung-Han L

May 23, 2020

I like this course, even though it adopts auto-grader instead of peer-grading. It requires more accurate of your code and more skill of programming, but it is worthy.

By Yufan L

Aug 1, 2019

A lot of self-learning. The assignment is challenging, but well designed! The forum is the key to understand the Computer science writing style in the assignment :)

By Sarah H H

May 20, 2019

Loved this course. the pacing, the instruction. it flowed and I felt i could execute what I learned without too much head scratching due 'missing leaps of info'.