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.
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
