Coursera - Pattern Discovery in Data Mining Review

Pattern discovery in data mining is the first course in a new 5-part data mining specialization offered by the University of Illinois at Urbana-Champaign through Coursera. Keeping with the trend of other specialization courses, pattern discovery in data mining spans 4 weeks and will likely be offered again each month or two after the first offering. The course covers a range of methods for finding different types of patterns in data, such as association rules and patterns in graphs. Grading is based exclusively on 4 weekly quizzes.

I was excited to see the new data mining specialization come up on Coursera to kick off 2015, but unfortunately, pattern discovery in data mining is a dull, poorly executed information dump. Besides an interesting topic, there’s not much going for this course. In the lectures, the professor reads information off dense slides and his delivery is more confusing than instructive. The slides, video and sound are of decent quality, but the explanations are not clear and while I normally don't have an issue with foreign accents, the professor's English made things harder to understand. To make things worse, there are few instructive in lecture quizzes and no activities or programming assignments. A course about data mining should have programming assignments or activities that let students interact with the concepts to reinforce learning. 

Pattern discovery in data mining is a disappointing start to the data mining specialization, that suffers from poor instruction quality and lack of illustrative assignments. Taking this course is like a data mining problem in and of itself: you have to spend a lot of time deciphering the lectures to uncover useful information.

I give this course 2 out of 5 stars: Poor.