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Learner Reviews & Feedback for Pattern Discovery in Data Mining by University of Illinois at Urbana-Champaign

4.2
214 ratings
44 reviews

About the Course

Learn the general concepts of data mining along with basic methodologies and applications. Then dive into one subfield in data mining: pattern discovery. Learn in-depth concepts, methods, and applications of pattern discovery in data mining. We will also introduce methods for data-driven phrase mining and some interesting applications of pattern discovery. This course provides you the opportunity to learn skills and content to practice and engage in scalable pattern discovery methods on massive transactional data, discuss pattern evaluation measures, and study methods for mining diverse kinds of patterns, sequential patterns, and sub-graph patterns....

Top reviews

GL

Jan 18, 2018

Excellent course. Now I have a big picture about pattern discovery and understand some popular algorithm. Also professor points out the direction for further study.

DD

Sep 10, 2017

The first several chapters are very impressive. The last three lessons are a little difficult for first-learners. The illustration are clear and easy to understand.

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26 - 44 of 44 Reviews for Pattern Discovery in Data Mining

By Tanan K

Apr 24, 2017

Should be more support in the forum for quiz and assignement

By Gary C

Jun 27, 2017

Excellent course that summarizes a very broad and complex topic. Definitely recommend.

By Tao Y

Feb 01, 2017

I learned a lot from this lecture. And I believe the lecture is excellent except that if he could become a little bit funny, then it would be perfect. Thanks,

Clark

By Jose A E H

May 02, 2017

It's an introductory course to key Pattern Discovery techniques with a comprehensive coverage of important subjects. However, it should be complemented by following the referenced material in order to obtain a wider and more complete picture of the field.

By Viorel B

Aug 09, 2019

Large variety of algorithm presented. Good study material recommendations. Fun assignments.

By Sergey

Feb 12, 2019

A good overview of data mining. The course turned out to be quite casual, with many quizzes requiring only knowledge of some definitions which disappeared from my short-lived memory in no time. I suppose it is based on a much more detailed and challenging one taught at the University of Illinois. On the other hand, programming assignments were fun.

By Devender B

Mar 06, 2019

One star less because of errors in the quiz questions which is not acceptable when it is mandatory to pass

By Raj A S

Apr 11, 2019

very time consuming

By Robert R

May 28, 2017

Solid introduction with a lot of references.

Lot of topics are not deep enough discussed and a lot of additional reading is necessary in order to get a lot out of the course. Furthermore, the presentation style and the (language) understandability of the lecturer are not very good. Too few exercise questions. Would still recommend it as introduction course and for the high number of good paper references.

By Logan J T

May 15, 2018

I would prefer to see this class split into two. I felt topics did not receive enough time to truly learn them. I would also like to see a more advanced course that required programming assignments.

By Limber

Nov 28, 2017

I don't really like the Programming Assignment of this course.

I have took over one month to figure it out, and the feedback system don't even provide me any help. The day that I have registered for this course, the coding is still new to me although I have got the training like 1 year thanks to Andrew Ng. And I could only used MATLAB/Octave or Python to solve the quiz. I have tried to use MATLAB to finished this course, but I failed many times. Finally, I have decided to use Python to solve this PA, and the algorithm is still hard for me to complete, so I used the python tool that with the algorithm in it and fix a little.

I believe that this course is a really good course, and Jiawei Han is a real kind person. BUT even for some other courses, we got a startup(like Andrew Ng's Machine Learning Course and Koller's PGM).

However, besides the PA, the rest of the course is really worth taking. I read the books for times and figured out that it indeed help! Though, it is hard for a new student. You should have to dive deep into the course which you should read more about this subject. Jiawei Han's work is only a startup.

Thank you very much.

By Aleksandra H

May 26, 2019

Briefly described a lot of stuff that could have been explained more visually and demonstrated with step-by-step examples more often. This might be expected for a 4-week course, but it would have been nice to extend it instead of trying to fit it into a compressed time frame. The required programming assignment could have been clearer about how the work should be structured and submitted.

By To P H

May 08, 2019

Course content too dense with many lectures serve as mere summary of advanced papers with little explanantion of technical terms. Too much mention of advanced topics with not enough coverage and depth for each topic

There are not many examples of the algorithm/of a case that can be solved using an algorithm. Little math is involved

Course should be longer (6 weeks) with longer lectures with more examples and exercises

This makes the content quick to be forgotten.

By sergey z

Mar 16, 2017

The explanations are not clear. The course is very theoretical, there's just one obligatory programming task. It's one of the worst courses I have ever enrolled in.

By Benoit P

Dec 31, 2016

Really disappointing. The slides contain a lot of paper references that seem to be of high quality (that's the reason I'm giving it 2 stars and not just 1)... but the course itself is bad: it covers many algorithms, but so superficially that you learn nothing; and there are not enough programming assignments to really allow you to get any intuition on the concepts.

I would love to see this be turned into a 5-course, 30-week specialization in itself (and the professor sure looks like he has the knowledge to fill these 30 weeks)... but as a single course over 4 weeks, it's not good.

By Thomas G

Feb 08, 2019

so hard to understand his english. only reading from slides not really explaining a lot or giving intuitions. Not happy with this course.

By Begoña

Jun 23, 2018

It's really hard to understand the explanations of the teacher. I gave up after the first week.

By Antoine G

Oct 22, 2016

A list of research papers to read further that's it. The course is too short to cover the subject so it covers nothing in the end.

The programming assignment have no help, whatsoever it's "do it" any language. The 2 programming assignment doesn't have much to do with the course. We don't even talk about the algo to use to do it. It looks like coursera has asked the professor to add a programming assignment to the course and he had 3 minutes to choose what it could be.

It shouldn't be advertised in coursera as it is.

Ah, forgot to mention that no one replies to the forums,actually no one uses them.

I think the subject is very interesting but this course gives a really bad advertising to Coursera, the university and the professor.

It needs more work before it's deployed on the platform.

I am going to try another Coursera course in the same kind of subject I hope it won't be the same.

By Lei Z

Dec 30, 2016

too theoretical without enough practical quiz and assignment