JCU Logo

James Cook University Subject Handbook - 2024

For subject information from 2025 and onwards, please visit the new JCU Course and Subject Handbook website.

CP5634 - Data Mining

Credit points:03
Year:2024
Student Contribution Band:Band 2
Administered by:College of Science and Engineering

Subject Description

    This subject focuses on advanced data mining techniques for intelligence informatics. It provides an in-depth coverage of the need for big data analysis, data warehousing, big data analytics, predictive methods, scalability considerations, data visualisation, and data mining techniques. Students will gain hands-on experience with various data mining tools and embedding data mining in intelligent informatics solutions.

Learning Outcomes

  • explain the importance of big data analysis and data mining
  • identify and critically evaluate data mining techniques and tools
  • compare and evaluate appropriate techniques for clustering, classification and association rules mining
  • assess the potential benefits, risks, issues and challenges associated with big data and data mining
  • explore and analyse data mining patterns for intelligence informatics

Subject Assessment

  • Written > Examination (centrally administered) - (40%) - Individual
  • Written > Test/Quiz 1 - (20%) - Individual
  • Written > Project report - (40%) - Group

Note that 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.

Inadmissible Subject Combinations:  CP3300 CP3403 CP5605

Availabilities

Cairns Nguma-bada, Trimester 1, Internal

Census date:Thursday, 22 Feb 2024
Study Period Dates:Monday, 29 Jan 2024 to Saturday, 27 Apr 2024
Coordinator(s):
DR Dmitry Konovalov
Lecturer(s):
DR Kyungmi Joanne Lee
Workload expectations:The student workload for this 3 credit point subject is approximately 130 hours.
  • 6 Hours - Workshops
  • 20 Hours - Seminars
  • 10 Hours - Online activity
  • 10 Hours - Specialised

JCU Brisbane, Trimester 1, Internal

Census date:Thursday, 22 Feb 2024
Study Period Dates:Monday, 29 Jan 2024 to Saturday, 27 Apr 2024
Coordinator(s):
DR Dmitry Konovalov
Lecturer(s):
DR Ahmed Fadhil
Workload expectations:The student workload for this 3 credit point subject is approximately 130 hours.
  • 6 Hours - Workshops
  • 20 Hours - Seminars
  • 10 Hours - Online activity
  • 10 Hours - Specialised

JCU Brisbane, Trimester 2, Internal

Census date:Thursday, 13 Jun 2024
Study Period Dates:Monday, 20 May 2024 to Saturday, 24 Aug 2024
Coordinator(s):
DR Dmitry Konovalov
Lecturer(s):
DR Ahmed Fadhil
Workload expectations:The student workload for this 3 credit point subject is approximately 130 hours.
  • 6 Hours - Workshops
  • 20 Hours - Seminars
  • 10 Hours - Online activity
  • 10 Hours - Specialised

JCU Brisbane, Trimester 3, Internal

Census date:Thursday, 10 Oct 2024
Study Period Dates:Monday, 16 Sep 2024 to Saturday, 14 Dec 2024
Coordinator(s):
DR Dmitry Konovalov
Lecturer(s):
DR Ahmed Fadhil
DR Paul Darwen
Workload expectations:The student workload for this 3 credit point subject is approximately 130 hours.
  • 6 Hours - Workshops
  • 20 Hours - Seminars
  • 10 Hours - Online activity
  • 10 Hours - Specialised

JCU Singapore, Study Period 51, Internal

Census date:Thursday, 07 Mar 2024
Study Period Dates:Thursday, 15 Feb 2024 to Friday, 26 Apr 2024
Coordinator(s):
DR Dmitry Konovalov
Lecturer(s):
DR Eric Tham
Workload expectations:The student workload for this 3 credit point subject is approximately 130 hours.
  • 6 Hours - Workshops
  • 20 Hours - Seminars
  • 10 Hours - Online activity
  • 10 Hours - Specialised

JCU Singapore, Trimester 2, Internal

Census date:Thursday, 13 Jun 2024
Study Period Dates:Monday, 20 May 2024 to Saturday, 24 Aug 2024
Coordinator(s):
DR Dmitry Konovalov
Lecturer(s):
MR Bahtee Eng
MR Ilia Tivin
Workload expectations:The student workload for this 3 credit point subject is approximately 130 hours.
  • 6 Hours - Workshops
  • 20 Hours - Seminars
  • 10 Hours - Online activity
  • 10 Hours - Specialised