Description

Data mining consists of a wide range of data analysis techniques that can be applied to large datasets to discover patterns, trends and other forms of knowledge embedded in the data. In the commercial world, data mining is often conducted on enterprise data stored in relational databases to help managers make informed decisions so as to keep businesses competitive and attuned to changing market conditions. With the recent advances in data generation and collection, new data types such as text, web, spatial, and temporal data have emerged creating new opportunities for mining knowledge from data for business intelligence.This course provides an introduction to the fundamental issues and basic techniques of data mining. The topics covered include data mining process, data preprocessing, data mining techniques and data mining evaluation. In particular, the use of data mining in support to business intelligence and decision making will be covered through labs, projects and case studies.Students are expected to learn data mining and its use in business intelligence through acquiring the basic data mining concepts and techniques, using them to explore data, and deriving useful knowledge patterns from the data through hands-on programming and experimentation that involve some industry strength data mining software packages.

Learning Outcomes

Graduate Learning Outcomes

Disciplinary Knowledge, Multidisciplinary Knowledge, Interdisciplinary Knowledge, Critical thinking & problem solving, Innovation and enterprising skills, Collaboration and leadership, Communication, Intercultural understanding and sensitivity, Understanding of global and Asian perspectives, Ethics and social responsibility, Understanding of sustainability issues, Self-directed learning

Competencies

Data Analytics, Business Environment Analysis, Business Innovation, Design Thinking Practice, Data Strategy