Course Review – Pattern Discovery in Data Mining (Jiawei Han, UIUC)

Here is my review of Feb-Mar 2015 incarnation on Coursera of Pattern Discovery, which is the first course in Data Mining specialization. Ranking is 2.2 out of 5 (bad), while I passed with 99.3% grade.

Technologies: Data Mining is the process of extracting knowledge from data.
The basic ideas and techniques are learnt: Apriori principle, frequent pattern growth, pruning, etc. Due to the absence of homework substantial efforts are needed to apply to real problems.

Material: the course presents foundations of data mining by describing the basic notions and their relations (pattern, knowledge, mining process) +
presenting a variety of efficient pattern discovery algorithms. The outlined applications are in text processing, network/graph knowledge discovery, and advertising.

Instructor/lectures: Jiawei Han is a world-leading researcher in data mining.
He is enthusiastic to describe the details of techniques, but frequent omissions/typos + lack of programming assignments make it challenging to fully understand and internalize the concepts.

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