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Unit of study_
QBUS6850: Advanced Machine Learning for Business
2025 unit information
Machine Learning is a crucial component of data analytics that automates analytical model building in modern business contexts. In today’s big data era, the ability to analyse vast and diverse data sources empowers organisations to make informed and data-driven decisions across various business domains. This unit covers a wide range of cutting-edge machine learning algorithms that learn from data, unveiling hidden patterns and relationships critical for strategic business decision making. Potential topics include: Neural Networks, Deep Learning, Text Analytics, Natural Language Processing, Advanced Ensemble Methods, Matrix Decomposition, and Recommender Systems. Emphasis is placed on practical applications involving the analysis of business data, allowing students to develop skills in applying machine learning techniques to solve real-world business challenges.
Unit details and rules
Managing faculty or University school:
Business (Business School)
| Study level | Postgraduate |
|---|---|
| Academic unit | Business Analytics |
| Credit points | 6 |
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Prerequisites:
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QBUS6810 |
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Corequisites:
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None |
| Prohibitions:
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None |
| Assumed knowledge:
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None |
At the completion of this unit, you should be able to:
- LO1. differentiate different types of learning algorithms and identify the advantages and limitations of each method
- LO2. build a strong machine learning skill set for business decision making
- LO3. create machine learning models for studying relationship amongst business variables
- LO4. work with various data sets and identify problems within real-world constraints
- LO5. demonstrate proficiency in the use of statistical software, e.g. Python, for machine learning model implementation
- LO6. work productively and collaboratively in a team
- LO7. present and write insights and suggestions effectively, professionally and ethically.
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 1 2024
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Normal day | Camperdown/Darlington, Sydney | |
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Semester 2 2024
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Normal day | Camperdown/Darlington, Sydney |
| Session | MoA ? | Location | Outline ? |
|---|---|---|---|
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Semester 1 2025
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Normal day | Camperdown/Darlington, Sydney |
Outline unavailable
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Semester 2 2025
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Normal day | Camperdown/Darlington, Sydney |
Outline unavailable
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Modes of attendance (MoA)
This refers to the Mode of attendance (MoA) for the unit as it appears when you’re selecting your units in Sydney Student. Find more information about modes of attendance on our website.
