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CP3300 - Knowledge Discovery and Data Mining

Credit points: 3
Year: 2012
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 knowledgge discovery in databases;
  • Develop data mining techniques using C++/Java;
  • Analyse large datasets using data mining techniques;
  • Use contemporary data mining suites.

Graduate Qualities

  • 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 lead, manage and contribute effectively to teams;
  • The ability to work individually and independently.
Prerequisites: CP1200 AND CP1500
Inadmissible
Subject
Combinations:
CP5605

Availabilities

Beijing UT, Study Period 68, Internal
Census Date 28-Jun-2012
Coordinator: Professor Ickjai Lee
Workload expectations:
  • 26 hours lectures
  • 12 hours tutorials
Assessment: end of semester exam (50%); presentations (10%); assignments (20%); report (20%).

Cairns, Study Period 2, Internal
Census Date 23-Aug-2012
Coord/Lect: Professor Ickjai Lee.
Workload expectations:
  • 26 hours lectures
  • 12 hours tutorials
Assessment: end of semester exam (50%); presentations (10%); assignments (20%); report (20%).

JCU Singapore, Study Period 52, Internal
Census Date 09-Aug-2012
Coordinator: Professor Ickjai Lee
Workload expectations:
  • 26 hours lectures
  • 12 hours tutorials
Assessment: end of semester exam (50%); presentations (10%); assignments (20%); report (20%).

Townsville, Study Period 2, Internal
Census Date 23-Aug-2012
Coordinator: Professor Ickjai Lee
Lecturer: Assoc. Professor Hossein Ghodosi.
Workload expectations:
  • 26 hours lectures
  • 12 hours tutorials
Assessment: end of semester exam (50%); presentations (10%); assignments (20%); report (20%).

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.