CP3300 - Knowledge Discovery and Data Mining

Credit points:	03
Year:	2010
Student Contribution Band:	Band 2
Administered by:	School of Business

This subject is an introduction to principles, techniques and applications of data mining and knowledge discovery. This subject covers a broad spectrum of data mining encompassing the basics of data mining, knowledge discovery in databases, preprocessing, data warehousing, scalable clustering, classification, ensemble, exploratory data analysis, market basket analysis, association rules mining and domain specific applications.

Learning Outcomes

• understand the working principles of data mining and knowledge discovery;
• understand the cutting-edge data mining technologies used to analyse large datasets;
• use contemporary data mining suites;
• analyse large datasets using data mining techniques.

Graduate Qualities

• The ability to adapt knowledge to new situations;
• The ability to define and to solve problems in at least one discipline area;
• The ability to think critically, to analyse and evaluate claims, evidence and arguments, and to reason and deploy evidence clearly and logically;
• The ability to deploy critically evaluated information to practical ends;
• The ability to find and access information using appropriate media and technologies;
• The ability to evaluate that information;
• The acquisition of coherent and disciplined sets of skills, knowledge, values and professional ethics from at least one discipline area;
• The ability to generate, calculate, interpret and communicate numerical information in ways appropriate to a given discipline or discourse;
• The ability to lead, manage and contribute effectively to teams;
• The ability to work with people of different gender, age, ethnicity, culture, religion and political persuasion;
• The ability to work individually and independently.

Prerequisites:	CP1200 AND CP1500
Inadmissible Subject Combinations:	CP5605

Availabilities
Townsville, Internal, Study Period 2
Census Date 26-Aug-2010
Coord/Lect:	Assoc. Professor Ickjai Lee.
Contact hours:	26 hours lectures 12 hours tutorials
Assessment:	end of semester exam (40% - 60%); presentations (10%); assignments (30% - 50%).
Cairns, Internal, Study Period 2
Census Date 26-Aug-2010
Coord/Lect:	Assoc. Professor Ickjai Lee.
Contact hours:	26 hours lectures 12 hours tutorials
Assessment:	end of semester exam (40% - 60%); presentations (10%); assignments (30% - 50%).
JCU Singapore, Internal, Study Period 52
Census Date 22-Jul-2010
Coordinator:	Assoc. Professor Ickjai Lee
Contact hours:	26 hours lectures 12 hours tutorials
Assessment:	end of semester exam (40% - 60%); presentations (10%); assignments (30% - 50%).

Note: Minor variations might occur due to the continuous Subject quality improvement process, and in case of minor variation(s) in assessment details, the Subject Outline represents the latest official information.