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

4.3
stars
2,660 ratings
508 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

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. :-)

BK

Jun 26, 2018

Would love to see these courses have more practice questions in each weeks lesson. Would be helpful for repetition sake, and learning vs only doing each question once in the assignments.

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26 - 50 of 501 Reviews for Applied Text Mining in Python

By RAUL E G

Apr 13, 2018

The professor needs to prepare students better for exams and assigments. Too few lectures.

By Xing W

Oct 28, 2017

The video is still in python 2. Very limited instructions.

By Aziz J

Dec 18, 2017

This class was fantastic. It was an order of magnitude times better than the previous course, 'Applied Machine Learning,' by Kevyn Collins-Thompson. Professor V. G. Vinod Vydiswaran started most lectures with a purpose and an alluring example. He spent a good amount of time building intuition behind the algorithms and techniques involved, and saved most of the coding for challenging and satisfying homework assignments--all qualities that the previous course did not have.

Finally, professor V. G. Vinod Vydiswaran was simply energetic about teaching. I didn't have to change playrate to > 1.2x. I genuinely enjoyed his teaching style.

This course has restored my faith in the 'Applied Data Science with Python' specialization by University of Michigan and I am confident in my ability solve text classification problems in Python. Highly recommended, along with the first two courses in this specialization.

By Vaibhav S

Jun 26, 2018

I never knew, that the data that is present over the internet can provide such fascinating details, from which we can infer a lot. The teaching methodology of Professor Vinod where he introduces to the very basic concepts of this course, and then slowly and steadily moves to some of the core concepts of NLP is really fantastic. This course gives you all the key ingredients you need to create advanced NLP projects using python programming language.

By Yusuf E

Apr 18, 2018

Very good overview of the NLP tasks. The assignments were again really challenging and required a lot of navigating the documentation and forums. The autograder is really frustrating sometimes though especially when it can't upload your file and you miss that part and change your correct code. Again, the assignments are really difficult without help from the forums but it was worth it.

By Maruf H

Oct 18, 2017

Short and concise introduction to text mining and natural language processing. The presentation of the instructor is very good. The course could be organized in a better way, more course material should be added. I like the assignments so much, they taught me a lot although I think there have some problem with the Grader. Overall it's a recommended course for a CS student.

By Kedar J

Nov 09, 2018

Great course! The assignments were at times hard to understand. Thanks to the wonderful support from the fellow students and mentors in the discussion forums, you will get most of the clarifications. Would recommend completing first 3 courses of this specialization before this one. There are a plenty of new concepts and new libraries introduced in this course.

By Milan B

May 08, 2020

I have been really interested in text mining for his wide applications. This course is very nice, it gives all the bases to deal with text mining problems! However, there could have been a Jupyther Notebook to put in applications the bases with Python about Topic Modeling in order to be more confortable for the Assignement 4.

By Yunfeng H

Mar 27, 2019

This is a very helpful courses for text mining. It starts with cleaning data and then gradually build up the skills to classify and group texts. I love all the case studies. The assistant walks me through the tasks using the tools and methodologies mentioned in the lectures. It also helps to solve the assignments.

By Daniel N

Sep 07, 2017

I enjoyed the course and have found the topics very interesting. One criticism is that the general quality of notebooks provided with example codes wasn't as high as for other courses in the specialization.However the lecturer was really nice and gave very good explanations even for complicated concepts.

By Γεώργιος Κ

Apr 24, 2018

The lessons are useful, and all of the knowledge is a must have. Some things could go deeper, some needed more explanation. As a result this is a must have course for text mining but I think that the level is introductory and in real world one must have more skills to perform a respected text mining.

By Jan Z

Sep 07, 2018

Great course overall. I have learned a lot, but last week had no tutorial example covering the topic and w4 assignment was not literally described resulting in spending a huge amount of time on trying which possible solutions will be accepted by autograder. Discussion forum helped a lot though.

By Víctor L

Feb 14, 2018

An excellent course, it gives a full introduction to text mining, what it is useful for, covers different techniques, provides challenging activities. Maybe it lacks of a practical activity in Week 4 before the assessment, but overall the course has very good content and an excellent instructor

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 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 12, 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 05, 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

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.