Monash University

Leader(s): Gippsland - Kai Ming Ting; Malaysia - Elsa Phung; South Africa - Neil Manson

Offered

Gippsland First semester 2009 (Day)
Gippsland First semester 2009 (Off-campus)
Sunway First semester 2009 (Day)
Singapore First semester 2009 (Off-campus)
South Africa First semester 2009 (Day)

Synopsis

In the modern corporate world, data is viewed not only as a necessity for day-to-day operation, it is seen as a critical asset for decision making. However, raw data is of low value. Succinct generalizations are required before data gains high value. Data mining produces knowledge from data, making feasible sophisticated data-driven decision making. This unit will provide students with an understanding of the major components of the data mining process, the various methods and operations for data mining, knowledge of the applications and technical aspects of data mining, and an understanding of the major research issues in this area.

Objectives

At the completion of this unit students will have gained knowledge of:

1. the motivation and the need for data mining;
2. characteristics of major components of the data mining process;
3. the basic principles of methods and operations for data mining;
4. case studies to bridge the connection between hands-on experience and real-world applications;
5. key and emerging application areas.

At the completion of this unit students will have gained understanding of current major research issues.

At the completion of this unit students will have gained skills in using data mining tools to solve data mining problems.

Assessment

Exam (3 hours): 60%; Assignments: 40%

Contact hours

one x 2hr lecture/week, one x 2hr tutorial/week

Prerequisites

FIT1004

Prohibitions

CSE3212, (Translation unit GCO3828)

Additional information on this unit is available from the faculty at:

http://www.infotech.monash.edu.au/units/fit3002