• Offered by Research School of Computer Science
  • ANU College ANU College of Engineering and Computer Science
  • Course subject Computer Science
  • Areas of interest Computer Science, Information Technology, Software Engineering
  • Academic career UGRD
  • Course convener
    • Dr Lexing Xie
  • Mode of delivery In Person
  • Offered in First Semester 2014
    See Future Offerings

This course examines the design of databases and data warehouses and their use for data mining; and investigates associated issues. Topics may include: relational theory and conceptual modelling; privacy and security; statistical databases; distributed databases; data warehousing; data cleaning and integration; and data mining concepts and techniques.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

On completion of this course, the students should have gained a good understanding of basic concepts, principles and techniques in data warehousing and data mining. Specifically, the students are able to perform the following tasks.

  • Perform data modeling
  • Apply OLAP techniques for mulit-dimensional data analysis
  • Apply datacubing techniques
  • Develop general skill of data warehousing project management
  • Obtain the general knowledge on the design and implementation of data warehouses
  • Be able to apply data mining techniques for knowledge discovery
  • Develop in-depth understanding of fundamental data mining algorithms
  • Perform data mining in data warehouses.

Indicative Assessment

Two assignments (40 marks); Final Exam (60 marks)

The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.

Workload

Thirty one-hour lectures and six two-hour tutorials

Requisite and Incompatibility

To enrol in this course you must have completed COMP2400 and 6 units of 1000 level COMP courses and 6 units of 2000 level COMP courses; and 6 units of 1000 level MATH courses or 1000 level STAT courses.

Prescribed Texts

The following text book will be used for this course:

  • Jiawei Han, Micheline Kamber, and Jian Pei,Data Mining:Concepts and Techniques, 3rd edition, Morgan Kaufmann, 2011 http://www.cs.uiuc.edu/~hanj/bk3/

Majors

Minors

Fees

Tuition fees are for the academic year indicated at the top of the page.  

If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Students continuing in their current program of study will have their tuition fees indexed annually from the year in which you commenced your program. Further information for domestic and international students about tuition and other fees can be found at Fees.

Student Contribution Band:
2
Unit value:
6 units

If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees.  Where there is a unit range displayed for this course, not all unit options below may be available.

Units EFTSL
6.00 0.12500
Domestic fee paying students
Year Fee
1994-2003 $1650
2004 $2190
2005 $2190
2006 $2190
2007 $2298
2008 $2592
2009 $2850
2010 $2916
2011 $2946
2012 $2946
2013 $2946
2014 $2952
International fee paying students
Year Fee
1994-2003 $3234
2004 $3234
2005 $3288
2006 $3426
2007 $3426
2008 $3426
2009 $3426
2010 $3750
2011 $3756
2012 $3756
2013 $3756
2014 $3762
Note: Please note that fee information is for current year only.

Offerings, Dates and Class Summary Links

The list of offerings for future years is indicative only.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.

First Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
3445 17 Feb 2014 07 Mar 2014 31 Mar 2014 30 May 2014 In Person N/A

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