RM
The course exercises are medium-hard. But the topic coverage is spot on.
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.
RM
The course exercises are medium-hard. But the topic coverage is spot on.
JG
OK course, some lectures with too much breadth at the cost of depth
VB
Good course, Faculty has excellent knowledge and well explaind
HX
Great data mining. Really having fun with the assignment.
TK
Should be more support in the forum for quiz and assignement
VB
Large variety of algorithm presented. Good study material recommendations. Fun assignments.
CY
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.
AS
Good course. The explanation for the optional programming assignment is very poor.
AD
Excellent introduction to pattern mining algorithms. I also like liked the fact that there are hands on assignments not just theory.
DD
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.
GC
Excellent course that summarizes a very broad and complex topic. Definitely recommend.
CY
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
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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.
I'd review this course for two parts: lectures and programming assignments.
Lectures: Prof. Jiawei Han is a pioneer of the subject. However, I was expecting a more indepth elaboration of techniques. In almost all his lectures he covered very crucial topics at a near-shallow level. For someone like me, it was a motivation to be learning the subject from him but I was left disappointed a little bit. I felt if i was just to gain a superficial understanding then I would have browsed through any website/blog/article rather than paying for this course and coming here under his tutelage. I will not expect him to be as thorough as he'd be in his lectures at UIUC (although why not!) but a more elaborative explanation with more notable examples (instead of pointing to the reading material at the end of 4th minute of the lecture) will be more fruitful and a better learning experience.
The programming assignments are challenging and will definitely open up the thought process towards being able to imagine what patterns mean and how to go about extracting them.
very unhelpful lecture, basically learn everything by yourself
Excellent introduction to pattern mining algorithms. I also like liked the fact that there are hands on assignments not just theory.
Useful course. It covers all the fundamentals of data mining patterns for a wide spectrum of datasets.
Very poor.
No programming assignment. No more users in forum. Lessons are just a list of algorithm without a detailed explanation.
Very well-organised course. I especially liked the assignments: programming assignments were helpful to apply the course (this makes you implement the methods you learn), so were multiple-choice questions that really make you think on the course content. The instructor was clear and provided good materials. I would recommend this course.
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.
It is really really hard to precede the course.
Explanation for each algorithms is insufficient.
If it offered many actual assignment like programming and making results, analyzing results,
this course can be better than now.
In this status, students can be confused because they don't know what they knew for this course and what these lectures explains.
The qualities of the assignments are quite low.
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.
so hard to understand his english. only reading from slides not really explaining a lot or giving intuitions. Not happy with this course.
It's really hard to understand the explanations of the teacher. I gave up after the first week.
too theoretical without enough practical quiz and assignment
compact class which teaches you lots of knowledge without wasting any time, using frequent tests to renew your memory and test your comprehension.
The programming assignment is a little bit challenging though. I would like to post a guide if I figure out how to get 100/100.
Gave a very good introduction of Pattern Discovery and different mechanisms/algorithms for pattern discovery. Talks about different pattern discovery approaches, pros & cons of each. Found it very helpful for my investment analysis project
Very well taught. The teacher has a very good understanding of the level of detail that can be addressed. He uses clear examples and keeps each lesson to the point. The quizzes are short and focussed on what was taught in the course.
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.
The course is very helpful and brings fascinating insights for projects.