Chevron Left
Pattern Discovery in Data Mining に戻る

イリノイ大学アーバナ・シャンペーン校(University of Illinois at Urbana-Champaign) による Pattern Discovery in Data Mining の受講者のレビューおよびフィードバック



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....



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.


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.


Pattern Discovery in Data Mining: 26 - 50 / 57 レビュー




by Mauricio B V


I like this course. Its provides a good base for pattern discovery, with useful high level techniques, this can be used as a starting point.

Something to improve can be incorporating at least one lesson with best practice coding techniques to solve the practical exercises.

by Jose A E H


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 Hidetake T


There are only two programming assignments. One more assignment will gives learners much more confidence I guess. But there are no other similar courses in MOOC. So, worth to take it.

by Clark Y


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,


by Cheng-shuo Y


It is a good course but more knowledge are expected to be filled, e.g, some algorithm can be detailed or illustrated with simple-case instantiation.

by 邓文豪


The course is relatively easy to understand and points out the direction for further study.

by V B


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

by Gary C


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

by Alexander S


Good course. The explanation for the optional programming assignment is very poor.

by Rahul M


The course exercises are medium-hard. But the topic coverage is spot on.

by Jaroslaw G


OK course, some lectures with too much breadth at the cost of depth

by Tanan K


Should be more support in the forum for quiz and assignement

by Lerata M


Sigh, algorithms are not a walk in the park!

by Piotr B


Too much material. Not enough real examples.

by Limber


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 To P H


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 Robert R


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 Aleksandra H


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 Sergey


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 Logan J T


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 Alan J R


Way too hard to find out whta the teacher was talking abut, had to make too much research on texts. Specially about CP-Miner. For the rest, great!

by Devender B


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

by Red R


C​ertain lectures unclear

by Raj A S


very time consuming