Comentários e feedback de alunos de Descobrindo padrões aplicáveis na mineração de dados da instituição Universidade de Illinois em Urbana-ChampaignUniversidade de Illinois em Urbana-Champaign

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 poor.

No programming assignment. No more users in forum. Lessons are just a list of algorithm without a detailed explanation.

very great！it's very helpful for me! thank you !

nice

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.

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.

Very interesting and very clearly explained.

Very usefull course. I learned too much about pattern discovering.

Great course for beginners without experience in Python programming

Amazing!

The course is very helpful and brings fascinating insights for projects.

very nice!

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.

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.

Nice work plan

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.

Excel

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

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

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.

Should be more support in the forum for quiz and assignement

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

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.

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.