Advanced Data Mining - 2018

To enrol in this unit, you must be accepted into a course from the provider. Read before you start

Unit summary

STA80005

  • Level of Study: Postgraduate
  • Study load: 0.125 EFTSL
  • Delivery method: Fully Online
  • Prerequisites: Yes
  • Duration: 13 weeks
  • Government loans available: FEE-HELP
  • Availability for 2017: SP3
  • Availability for 2018: SP3
  • Assessment: Assignments - 2 (40%) , Invigilated Exam (50%) - Learn more

Unit provided by

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2018 Fees
AUD$
Domestic 2,830.00
Domestic continuing 2,620.00
International 3,080.00
International continuing 2,870.00

Tuition fees are reduced for continuing registered SWI students.
Please login to view the applicable amount.

Please note: this unit was previously titled Statistical Marketing Tools

This unit introduces the principles and techniques used by data miners. Data mining is used to add value to large collections of data, delivering discoveries that continue to revolutionise lives in our data-rich but knowledge-hungry world.

Please note: assessment values are indicative only, details will be advised at the start of the unit.

Students who successfully complete this unit will be able to:

  1. Formulate an understanding of the basic theory and principles of data mining
  2. Assess prediction and classification methods such as regression, neural networks and decision trees, understanding how to choose between these methods
  3. Evaluate unsupervised data mining methods and determine when these methods should be combined with supervised methods
  4. Design ontologies based on text and creative visualisations of textual relationships
  5. Report on the results of specific data mining projects.
  • Assignments — 2 (40%)
  • Invigilated Exam (50%)
  • Quizzes — Online (10%)
For more information on invigilated exams see Exams and results

Equivalent units

You cannot enrol in this unit if you have successfully completed any of the following unit(s) because they are considered academically equivalent:

  • HMS794 — Statistical Marketing Tools

Mandatory prerequisites

You must have successfully completed the following unit(s) before starting this unit:

If you have completed equivalent study at another university, please contact a Student Advisor for advice.

  • Other special requirement — You will require access to a recent version of SPSS and the latest version of SAS Enterprise Miner. Note: SAS will only run on a Windows platform.

In order to enrol in this unit, you must be accepted into one of the following courses:

Please visit the course details page and read the Requirements tab for more information about eligibility.

This unit addresses the following topics.

NumberTopic
1Introduction to data mining and a data mining package
2Linear Models
3Classification and regression trees
4Random forests and boosting
5Self-organising maps
6Cluster analysis
7Memory Based Reasoning
8Support Vector Machines
9Text Mining

This unit is delivered using the following methods and materials:

Instructional Methods

  • Discussion Forum/Discussion Board
  • Online Quizzes/Tests
  • Online assignment submission
  • Podcasting/Lecture capture
  • Standard Media
  • Web links

Print based materials

  • Welcome Letter

Online materials

  • Printable format materials

This unit is a core requirement in the following courses:

This unit may be eligible for credit towards other courses:

  1. Many undergraduate courses on offer through OUA include 'open elective' where any OUA unit can be credited to the course. You need to check the Award Requirements on the course page for the number of allowed open electives and any level limitations.
  2. In other cases, the content of this unit might be relevant to a course on offer through OUA or elsewhere. In order to receive credit for this unit in the course you will need to supply the provider institution with a copy of the Unit Profile in the approved format, which you can download here. Note that the Unit Profile is set at the start of the year, and if textbooks change this may not match the Co-Op textbook list.

Textbook information for this unit is currently being updated and will be available soon. Please check back regularly for updates. Alternatively, visit the The Co-op website and enter the unit details to search for available textbooks.

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