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Unit of study_
QBUS3820: Machine Learning and Data Mining in Business
2024 unit information
Advances in information technology have made available rich information data sets, often generated automatically as a by-product of the main institutional activity of a firm or business unit. Data Mining deals with inferring and validating patterns, structures and relationships in data, as a tool to support decisions in the business environment. This unit offers an insight into the main statistical methodologies for the visualisation and the analysis of business and market data, providing the information requirements for specific tasks such as credit scoring, prediction and classification, market segmentation and product positioning. Emphasis is given to empirical applications using modern software tools.
Unit details and rules
Managing faculty or University school:
Business Analytics
| Code | QBUS3820 |
|---|---|
| Academic unit | Business Analytics |
| Credit points | 6 |
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Prerequisites:
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QBUS2820 |
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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. demonstrate the knowledge of statistical theory required for business data mining and data analysis
- LO2. identify which statistical tool is most relevant for specific business analytics tasks
- LO3. identify the advantages and limitations of each method
- LO4. extract information from large volumes of data readily available from the business environment
- LO5. obtain and interpret a meaningful analytical result using a software package such as Python
- LO6. work productively in a team
- LO7. present and write about their findings effectively.
Unit availability
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Modes of attendance (MoA)
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