ITEC632 - Applied Data Mining

Year

Credit points

Campus offering

Prerequisites

ITEC622 Data Analytics and Visualisation

Teaching organisation

150 hours over a twelve-week semester or equivalent study period

Unit rationale, description and aim

Organisations across various sectors increasingly realise the benefits of exploiting the enormous data they collect and store to generate useful knowledge. Data mining is the process of discovering meaningful patterns in large data sets. Data mining utilises techniques from various fields including Statistics, Machine Learning, Artificial Intelligence, and Database Systems to transform data into a comprehensible structure.

In this unit students will learn the foundational data mining concepts and techniques for various data mining tasks such as predictive modelling, association analysis, cluster analysis and anomaly detection. Also, this unit develops students’ practical skills in applying data mining tools (e.g. RapidMiner) to perform data mining tasks on real-world datasets.

The primary aim of this unit is to equipping students with the knowledge and skills required to perform data mining using state-of-the art techniques and technologies in to solve the real-world problems and enable informed decision making considering ethical perspectives.