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Unit of study_
QBUS6850: Machine Learning for Business
2024 unit information
Machine Learning is a fundamental aspect of data analytics that automates analytical model building in modern business. In the big data era, managers are able to use very large and rich data sources and to make business decisions based on quantitative data analysis. Machine Learning covers a range of state-of-the-art methods/algorithms that iteratively learn from data, allowing computers to find hidden patterns and relationships in such data so as to support business decisions. This unit introduces modern machine learning techniques and builds skills in using data for everyday business decision making. Topics include: Machine Learning Foundation; Modern Regression Methods; Advanced Classification Techniques; Latent Variable Models; Support Vector Machines (SVM) and Kernel Methods; Artificial Neural Networks; Deep Learning; and Machine Learning for Big Data. Emphasis is placed on applications involving the analysis of business data. Students will practise applying machine learning algorithms to real-world datasets by using an appropriate computing package.
Unit details and rules
Managing faculty or University school:
Business Analytics
| Code | QBUS6850 |
|---|---|
| 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 |
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.
