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Unit of study_
OCMP5318: Machine Learning and Data Mining
2025 unit information
Machine learning is the process of automatically building mathematical models that explain and generalise datasets. It integrates elements of statistics and algorithm development into the same discipline. Data mining is a discipline within knowledge discovery that seeks to facilitate the exploration and analysis of large quantities for data, by automatic and semiautomatic means. This subject provides a practical and technical introduction to machine learning and data mining. Topics to be covered include problems of discovering patterns in the data, classification, regression, feature extraction and data visualisation. Also covered are analysis, comparison and usage of various types of machine learning techniques and statistical techniques.
Unit details and rules
Managing faculty or University school:
Engineering
| Study level | Postgraduate |
|---|---|
| Academic unit | Computer Science |
| Credit points | 6 |
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Prerequisites:
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None |
|---|---|
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Corequisites:
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None |
| Prohibitions:
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COMP5318 or COMP4318 |
| Assumed knowledge:
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Experience with programming and data structures as covered in COMP2123 or COMP2823 or COMP9123 (or equivalent unit of study from different institutions). Discrete mathematics and probability (e.g. MATH1064 or equivalent); linear algebra and calculus (e.g. MATH1061 or equivalent) |
At the completion of this unit, you should be able to:
- LO1. Students will be able to describe the basic principles, strengths, weaknesses and applicability of machine learning algorithms for solving classification, regression, clustering and reinforcement learning tasks.
- LO2. Students will be able to design machine learning algorithms through practical experience in designing, implementing and evaluation machine learning algorithms.
- LO3. Students will be able to design machine learning algorithms for solving classification, regression, clustering, and reinforcement learning tasks using machine learning software and libraries.
- LO4. Students will be able to present and interpret data and information in verbal and written form.
Unit availability
This section lists the session, attendance modes and locations the unit is available in. There is a unit outline for each of the unit availabilities, which gives you information about the unit including assessment details and a schedule of weekly activities.
The outline is published 2 weeks before the first day of teaching. You can look at previous outlines for a guide to the details of a unit.
| Session | MoA ? | Location | Outline ? |
|---|---|---|---|
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Semester 1a 2024
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Online | Online Program | |
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Semester 2a 2024
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Online | Online Program |
| Session | MoA ? | Location | Outline ? |
|---|---|---|---|
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PG Online Session 1A 2025
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Online | Online Program |
Outline unavailable
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PG Online Session 2A 2025
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Online | Online Program |
Outline unavailable
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Modes of attendance (MoA)
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