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.

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The course is hosted on the FutureLearn platform.:
More Data Mining with Weka

Students will work with multimillion-instance datasets, classify text, experiment with clustering, association rules, neural networks, and much more.

A new session starts on 3 October 2016, and the course will run in self-paced unsupported mode until 3rd January; whereupon Statements of Completion will be produced and mailed out. Students should have completed Data Mining with Weka (which will precede it), or have equivalent knowledge of the subject.

The course features:

- online access to chapters from Data Mining (3rd Edition)

- a detailed syllabus

- CC-BY videos & slides (see the materials site)

- online assessment leading to a Statement of Completion (example)

- English & Chinese captions on YouTube and Youku

Schedule

Pre-course survey

Class 1 - Exploring Weka's interfaces, and working with big data

Class 2 - Discretization and text classification

Mid-course assessment

Class 3 - Classification rules, association rules, and clustering

Class 4 - Selecting attributes and counting the cost

Class 5 - Neural networks, learning curves, and performance optimization

Post-course assessment

Post-course survey