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Learner Reviews & Feedback for Text Mining and Analytics by University of Illinois at Urbana-Champaign

4.5
stars
720 ratings

About the Course

This course will cover the major techniques for mining and analyzing text data to discover interesting patterns, extract useful knowledge, and support decision making, with an emphasis on statistical approaches that can be generally applied to arbitrary text data in any natural language with no or minimum human effort. Detailed analysis of text data requires understanding of natural language text, which is known to be a difficult task for computers. However, a number of statistical approaches have been shown to work well for the "shallow" but robust analysis of text data for pattern finding and knowledge discovery. You will learn the basic concepts, principles, and major algorithms in text mining and their potential applications....

Top reviews

JH

Feb 9, 2017

Excellent course, the pipeline they propose to help you understand text mining is quite helpful. It has an important introduction to the most key concepts and techniques for text mining and analytics.

DC

Mar 24, 2018

The content of Text Mining and Analytics is very comprehensive and deep. More practise about how formula works would be better. Quiz could be not tough to be completed after attending every lectures.

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76 - 100 of 145 Reviews for Text Mining and Analytics

By RAM K

Aug 23, 2020

excellent course

By aditya r

Dec 13, 2020

its nice course

By Raja R

Jan 22, 2021

Great Course!

By VIKAS M

Dec 16, 2020

fun learning

By Manikant R

Jun 21, 2020

great course

By David O

Jul 1, 2018

Great course

By 2003 A

Aug 31, 2023

good course

By 黄莉婷

Dec 27, 2017

讲的很不错,受益匪浅。

By Florov M

Apr 3, 2020

Excellent!

By Kamlesh C

Aug 23, 2020

Thank you

By Kumar B P

May 8, 2020

Excellent

By Assoc.Prof., C V T C

Apr 29, 2020

excellent

By MItrajyoti K

Oct 24, 2019

Very good

By 2K18/SE/129 V K

May 9, 2022

good one

By Hernán C V

May 4, 2017

Awesome!

By Arefeh Y

Nov 4, 2016

Great!!

By kalashri

Aug 24, 2023

great

By Swapna.C

Jul 17, 2020

nice

By Mrinal G

May 20, 2019

Nice

By Dr. I M

Jan 2, 2018

T

By Valerie P

Jul 11, 2017

E

By Deepak S

Aug 11, 2016

E

By Jennifer K

Jul 5, 2017

Despite the amount of material to cover, this course did a great job of introducing the right amount of detail for various aspects (motivation, algorithms, algorithmic reasoning, evaluation) on topic modelling, text clustering, text categorization, sentiment analysis, aspect sentiment analysis, evaluation of text and non-text data in context, and more. Definitely read the additional resources for the material - it will give you an incredibly in-depth view to what you learned in the lectures and also give you a start on implementing the covered algorithms on your own.

The only thing I missed in this class are assignments for implementing the algorithms in a language other than C++ and in a framework other than MeTA. It would make sense to provide this opportunity in additional, commonly-used data-science languages such as Python!

By Milan M

Sep 14, 2016

This is an excellent course that captures many different text mining techniques. It requires some math knowledge in numerical analysis and probability in order to understand the concepts.

I gave 4 star rating due to 2 problems during the course:

1) Lack of examples along the formulas and principles. There are some, but many concepts could be adopted much faster if examples were introduced right along with them.

2) The optional programming exercises are easy to complete, but the environment is very confusing to set it up.

By Gonzalo d l T A

May 10, 2017

A really interesting course which covers theoretically most of the text mining techniques. I missed having more practical exercise, which could help to deeply understand the lectures. Setting up the environment for the development task is a little bit complicated, it might be interesting to provide a virtual machine with all the software and correct versions required. Even though, I would recommend this course if you are interested on the topic.