This course follows on from Data Mining with Weka and provides a deeper account of data mining tools and techniques. Again the emphasis is on principles and practical data mining using Weka, rather than mathematical theory or advanced details of particular algorithms. Students will work with multimillion-instance datasets, classify text, experiment with clustering, association rules, neural networks, and much more.
Prosecompleted this course, spending 4 hours a week on it and found the course difficulty to be medium.
Another well thought-out Weka course from Waikato covering further areas of data mining (association rules, clustering, text classification, cost-sensitive techniques), of Weka (experimenter & knowledge flow interfaces) and of the data mining evaluation process (ROC, learning curves).
Assessments are fiddly, with a strong applied emphasis, but not too hard.
Current session closes 15/4/16, with an 'Advanced' follow-up course scheduled for late April (per Dr Witten's forum comments)