161.777 Practical Data Mining (15 credits)

A practical approach to data mining with large volumes of complex data; prepare, cleanse and explore data; supervised and unsupervised modelling with association rules and market basket analysis, decision trees, multi-layer neural networks, k-nearest neighbours, k-means clustering and self-organising maps, ensemble and bundling techniques, text mining; use of leading software tools; business examples and research literature.

Note(s): Access to a Windows PC is required for analysis of data.

Requirements Requirements help

Note: You may enrol in a postgraduate course (that is a 700-, 800- or 900-level course) if you meet the prerequisites for that course and have been admitted to a qualification which lists the course in its schedule.

Offerings Offerings help

Year Semester Mode Location
2021 Semester One full semester Block Auckland Campus
2021 Semester One full semester Distance