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

4.2
2,165 ratings
409 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 27, 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 04, 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. :-)

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151 - 175 of 401 Reviews for Applied Text Mining in Python

By Aashima B

May 07, 2019

Got to learn a lot. Would recommend it to others for text mining.

By Neville M

Aug 22, 2019

Does exactly what it says on the label. Makes you really think about what you are doing with the text. Highly recommended.

By Venelin K

Aug 25, 2019

Great course!

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 laurent.bilke@gmail.com

Sep 17, 2019

Great course. Does cover a lot of ground on the topic. The assignments are challenging, as should be.

By Halil K

Oct 02, 2019

Excellent course. Teaches useful knowledge and skills and does it with a very good teaching staff.

By Vinayak

Oct 08, 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 Joe

Sep 25, 2019

Really good overview, with just the right amount of detail

By Jahir M

Nov 18, 2019

it gives you the right things to start making models to extract information without getting too technical.

By Shiomar S C

Oct 23, 2019

Really good course... The teacher is great

By Timothy P

Nov 27, 2019

Challenging but fun class, I learned a lot. Much to build on and keep learning about. Thanks

By Abdul K S

Dec 03, 2019

Very nice and interactive course learnt a lot and the assignments are very good and very importing topics covered.

By Emanuele G

Nov 14, 2019

Excellent course

By Lalit S

Jan 29, 2019

Awesome

By Kristin A

Jan 30, 2019

A good intro to NLTK and text mining in Python, though sometimes the effort put in to render an assignment acceptable to the autograder was a headache.

By Utkarsh T

Dec 18, 2018

NA

By CaitlinYao

Feb 17, 2019

The assignments are much harder than the slides, which means much more self-learning is required.

By Muhammad S J

Mar 08, 2019

Overall course is very usefull for me. But there is lot of detail is missing in week 4. Wordnet and Gensim usage, Detail about the LDA and semantic similarity. I hope next time there is separate video lecture for detailed about Semantic simalarity.

By Roberto L L

Mar 01, 2019

This an excellent course to open a door for NLP, an exciting topic.

By Michael M

Mar 22, 2019

Great course. Auto graders have some issues.

By Christian E

Mar 27, 2019

Very good content

By Darius T

Apr 02, 2019

The course material is good. The main issue with this course are some of the assignments, which are pretty complicated, are not explained well enough and sometimes don't even test the knowledge of understanding text mining.

By Lucas S R

Feb 08, 2019

The course presented a good content for beginners in NLP and I feel confident to start using what I learned in my work. But, the grader for the assignments is too slow and buggy, this should be fixed so new learners don't feel frustrated. In addition, for assignment 4, the lda trainning parameters are not viable for trainning in coursera's environment, it should be reviewed.

By Alexander G

Jan 13, 2019

It would help to connect the teaching better to the assignments. Especially in Week 4 there is to little connection. There is not even a course notebook to practice some of the material.

By Ayush A

Jul 14, 2018

The course was good, but as I progressed in the course, the approach for code began slackening off, as it felt to me. Topics are discussed well, but the implementation in code was something that took a star away.