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

4.2
stars
3,784 ratings

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!

JR

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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401 - 425 of 737 Reviews for Applied Text Mining in Python

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 James M

Sep 28, 2020

The instruction and explanation of key concepts was fantastic, but the instruction on the actual coding was very lacking, even compared with the other courses in this specialization.

By Jeremy L

Oct 26, 2017

The course itself is good, but the assigment system is not robust and some sentences are also ambiguous to users. Seeing from the forums, many users get confused in the assigments.

By Aswath M

Aug 2, 2019

Excellent course for someone like me who is ambitious and aspires to gain knowledge on new things. The videos can be made bit more elaborate, seems to be rushing towards the end.

By Christopher H

Aug 11, 2018

Passionate instructor and a great primer on how software can infer useful data from text. Gives a preliminary understanding on the algorithms used in scikit learn and nltk.

By Vishal L

Dec 27, 2020

It is a great course with challenging assignments, I wish the syllabus is a little more deeper specially on the LDA part. But overall a good course that one can look for!

By Kangqiao

Nov 4, 2019

A little bit stretched my python skill, but learned a lot. Forum is a good place, and maybe next I will join some study group online or offline to have more discussions.

By Ramon S

Jan 23, 2021

Good Course, the only problem was in week 3 the sklearn method roc_curve() is used incorrectly and then in the assignment you need to use this method incorrectly again.

By C-y T

Jan 12, 2020

The course content and the assignments are good. Some descriptions of the assignment questions are ambiguous. The discussion forum is helpful in clarify those issues.

By TEJASWI S

Aug 1, 2019

Good course to take although I felt the course could have been better in terms of practice. But overall, would recommend to others if they wish to pursue data analysis.

By cheting c

Jun 22, 2018

Overall good class but the assignment design is somehow bad. Should give some hint otherwise we do not know if we get a wrong answer or the autogarder is not working.

By Vinicius G

Dec 26, 2017

I did not give 5 starts because Assignment 4 was really hard. It required too much knowledge from outside. The week 4 modules poorly prepared me for assignment 4.

By Kai H

Nov 5, 2018

Some of the codes are not shown in Jupyter notebook. The assignment statements are not so clear, need to resort to Discussion board for additional information.

By Glenn U

Jan 30, 2023

Good course subject matter, and well explained in the videos. But problems with the assessments' automated grading system do cause some unwanted frustrations.

By Ivan S F

May 3, 2019

Great course. Worth taking it. Hard, but you will learn a lot. Homework 1 is confusing and discouraging, but pass it and the rest gets more interesting.

By Han C

Sep 1, 2017

Learned lots of new stuff, but some details are not established well including autograder issue at the last assignment. Hope this gets cleared out soon.

By Kristin A

Jan 29, 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 Mauro G

Oct 3, 2017

The lectures are in my opinion too concise. The programming assignments are very interesting. Perhaps the week 1 programming assignment is too complex.

By Gerardo J I V

Mar 30, 2021

I had the opportunity of use the learned in this course for a project in my work about RPA with python, specifically for process a big volume of data.

By Vatsal B

Jun 5, 2020

Kindly provide all lecture codes as Jupyter Notebook file for each module. It helps a lot for revision. Overall an informative and excellent course.

By Showmik D

May 24, 2020

Its still an elementary course for natural language processing . May be the maths behind the algorithms and topics should be discussed elaborately .

By Fang F

Aug 29, 2017

Course is introductory and helpful. The staff should provide all the jupyter notebook code examples and provide better instruction for assignments.

By Asad M

Jan 19, 2020

Course is good but doesn't cover the whole lot of topics. the instructor is very good and clear. I expected to learn more advanced topics though.

By Alireza F

Sep 16, 2019

I believe that assignments are away harder than the material of the course. The instructor should more get involved in the codes when he teaches.

By Abdulkareem U

Apr 28, 2021

This is a very fantastic fundamental Natural Language Processing Tutorial, It was nice, awesome and I wish to learn more with Michigan Online.