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CP5634 - Data Mining
Credit points: |
3 |
Year: |
2023 |
Student Contribution Band: |
Band
2 |
Administered by: |
College of Science and Engineering |
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.
Inadmissible Subject Combinations:
|
CP3300 CP3403 CP5605 |
Availabilities
|
Cairns,
Study Period 1,
Internal
|
Census Date 23-Mar-2023 |
Coord/Lect: |
Dr Dmitry Konovalov. |
Workload expectations: |
The student workload for this
3
credit point subject is approximately
130 hours.
- 26 hours lectures
- 6 hours workshops
- 12 hours specialised
- assessment and self-directed study
|
|
|
JCU Brisbane,
Trimester 1,
Internal
|
Census Date 09-Mar-2023 |
Coordinator: |
Dr Dmitry Konovalov |
Lecturer:
|
Dr Ahmad Abdel-Hafez. |
Workload expectations: |
The student workload for this
3
credit point subject is approximately
130 hours.
- 26 hours lectures
- 6 hours workshops
- 12 hours specialised
- assessment and self-directed study
|
|
|
JCU Brisbane,
Trimester 2,
Internal
|
Census Date 22-Jun-2023 |
Coordinator: |
Dr Dmitry Konovalov |
Lecturer:
|
Dr Paul Darwen. |
Workload expectations: |
The student workload for this
3
credit point subject is approximately
130 hours.
- 26 hours lectures
- 6 hours workshops
- 12 hours specialised
- assessment and self-directed study
|
|
|
JCU Brisbane,
Trimester 3,
Internal
|
Census Date 05-Oct-2023 |
Coordinator: |
Dr Dmitry Konovalov |
Lecturer:
|
Dr Paul Darwen. |
Workload expectations: |
The student workload for this
3
credit point subject is approximately
130 hours.
- 26 hours lectures
- 6 hours workshops
- 12 hours specialised
- assessment and self-directed study
|
|
|
JCU Singapore,
Study Period 51,
Internal
|
Census Date 06-Apr-2023 |
Coordinator: |
Dr Dmitry Konovalov |
Lecturer:
|
Dr Eric Tham. |
Workload expectations: |
The student workload for this
3
credit point subject is approximately
130 hours.
- 26 hours lectures
- 6 hours workshops
- 12 hours specialised
- assessment and self-directed study
|
|
|
JCU Singapore,
Study Period 52,
Internal
|
Census Date 03-Aug-2023 |
Workload expectations: |
The student workload for this
3
credit point subject is approximately
130 hours.
- 26 hours lectures
- 6 hours workshops
- 12 hours specialised
- assessment and self-directed study
|
|
|
Townsville,
Study Period 1,
Internal
|
Census Date 23-Mar-2023 |
Coord/Lect: |
Dr Dmitry Konovalov. |
Workload expectations: |
The student workload for this
3
credit point subject is approximately
130 hours.
- 26 hours lectures
- 6 hours workshops
- 12 hours specialised
- assessment and self-directed study
|
|
|
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.