AMS3640 - Data Mining
|Year of Study:||3 - 4|
|Prerequisites:||(1) AMS1001 Introduction to Linear Algebra and Calculus, AMS1301 Foundations of Data Science (or AMS1303 Probability and Statistics), and AMS2640 Statistical Computing in Practice; or (2) With the Instructor’s permission and upon endorsement of the relevant Head or Programme Director.|
This module aims to provide students with the data mining techniques for solving practical problems. Students will learn a set of tools (e.g, SAS, R, Weka, Tableau) for data visualization and apply data mining techniques such as classification and association rules, cluster analysis and dimensionality reduction to analyse real-life problems. Students are required to work effectively in a team to complete a project.
Upon completion of this module, students should be able to:
- examine the significance of knowledge discovery process, data quality and preprocessing;
- apply visualization techniques for effective communication;
- apply data mining skills and techniques;
- interpret and present the results in a scientific and concise manner; and work effectively in a team and solve real-life problems.