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

4.3
stars
3,287 ratings
622 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. :-)

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551 - 575 of 614 Reviews for Applied Text Mining in Python

By Casey T

Oct 20, 2018

This course was not particularly well put together. I found the erratic behavior of the autograder for assignments to be a significant barrier to learning. This course was far more about battling data structures and python libraries than it was about text mining. The word "Applied" in the title should be replaced with "VERY VERY APPLIED..."

By Steven G

Nov 6, 2019

Confusing explanations of NLP concepts. Inadequate explanations of how to use the Python packages to solve the assignment questions. I'm writing this review half-way through the Applied Social Networks Analysis course which is excellent and pitched just right. The contrast between the 2 courses couldn't be greater.

By Gonzalo P O

May 14, 2019

Los ejercicios de este curso tienen una dificultad muy superior a lo mostrado durante las clases, lo que hace que uno deba de invertir mucho tiempo en los mismos investigando en recursos internos. Por ejemplo, con una dedicatoria semanal de 10-15 horas me llevó 2 meses enteros hacer el curso.

By Saravanan C

Aug 12, 2017

Liked the simplified content. But minimalist approach w.r.to coverage of concepts - could be better. Tactical/Operational support, responsiveness from the TA w.r.to confusions on questions or grader can significantly improve. Thanks for the course, I learnt and enjoyed the hands-on sessions.

By li m

Oct 28, 2018

I am kind of disappointed of this course especially the lecturer were talking too much than showing the practical examples, for example 'topic modelling'. With a few slides of introduction about topic modelling showing some lines of code without any examples in notebook isn't helping a lot.

By Yohann W

Apr 27, 2020

Disappointing compared to the other courses of this specialisation. Some concepts were not defined (i.e bag of words) for the assignment. A lot of errors in auto graders, assignments. I had the impression to have a list of concepts and functions without a real explanation.

By Raul M

Jun 2, 2018

I didn't like too much the structure of the lecture and the assignments, I don't think they were aligned that well. Also, I'm not sure how I'm going use this in real life.

The additional lectures were TOO MUCH theory which is not the purpose of the specialization.

By VenusW

Aug 25, 2017

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.

By Jared H

Feb 27, 2020

Poorly constructed course overall. Covers some key topics so may still be worthwhile but lectures and assignments do not match up, expectation is that you just Google the material to complete assignments. Could do that without signing up for a course.

By Lin Y

Jul 16, 2019

This course is probably the worst amongst all other courses in this specialization. The term 'applied' in the course title makes you think that this course helps you to build practical experiences in text mining. However, not true at all.

By Fabrice L

Aug 9, 2017

This course repeat a lot what we have seen in the module 3 of the specialization. There is not enough coding examples and the first assignment is not well design. The lectures doesn't prepare you enough to tackle the assignments.

By Muhammad H

Jul 16, 2020

Exercises are pretty good and give you a lot of practice however the instructor is far below par. Just reading out the slides like a typical private uni teacher. I doubt if he could pass the assignments of this course.

By Vincenzo T

Apr 27, 2019

Course is very interesting. However, getting your assignments right is extremely annoying. Sometimes you have no idea why it's not right. Every upload you need to change the type of your upload.

By Goh S T

Jun 16, 2020

course materials are minimal and possible insufficient to complete assignments without additional reading materials. Assignment questions can be clearer with sample output will be very helpful.

By Farzad E

Mar 17, 2019

It gives you a better understanding of SVM and LDA after taking the third course but they have failed to provide enough examples and exercises. Not every module has a notebook unfortunately!

By Samuel K

Jun 22, 2019

Good course with great content and lecturer however the assignments are all buggy and don't run in the Jupyter notebooks. This is frustrating to deal with in a paid course. Please fix!

By Cong L

Mar 22, 2018

Lecture was long-winded and could not hit the main points. Assignment was difficult without many explanation. Tutors were more humiliating students rather than providing supports.

By Svitlana K

Jul 29, 2019

Worst course in the specialization so far. Tasks in the assignments are very poor written and are unclear. Just listening lectures don't help you to complete your assignments.

By Dan H

Mar 29, 2020

There were significant issues with the autograder and the instructions for the programming assignments. This course has been around for a while. Why aren't they fixed???

By Shikhar S

Jun 6, 2019

The content of the course was quite good. But the level of teaching was a way too less than the level of Assignments. Ist assignment was too difficult to perform..

By Tal Y

Feb 18, 2018

The course takes you through the important NLP topics, the instruction is decent, but the assignments are clunky and waisted many hours of my time unproductively.

By Lovi R G

Oct 20, 2020

The assignments were far more beyond the content covered, hopefully either the content covered to be extended or the assignment scope to be changed.

By chris l

Jan 30, 2020

A lot of prior knowledge or independent learning is required to get the most out of this course. Needs more code walkthroughs.

By Stanley C

May 15, 2019

Assignment grading is way too rigid and not reflective of real world issues. It can be very frustrating.

By carol a

Oct 23, 2019

Instructions for assignments are vague and incorrect. Instructor was hard to follow during lecture.