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Unit of study_

QBUS6810: Statistical Learning and Data Mining

2024 unit information

It is now common for businesses to have access to very 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 visualization and the analysis of business and market data. It provides the tools necessary to extract information required for specific tasks such as credit scoring, prediction and classification, market segmentation and product positioning. Emphasis is given to business applications of data mining using modern software tools.

Unit details and rules

Managing faculty or University school:

Business Analytics

Code QBUS6810
Academic unit Business Analytics
Credit points 6
Prerequisites:
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(ECMT5001 or QBUS5001 or STAT5003) and (a mark of 65 or greater in BUSS6002 or COMP5310 or COMP5318)
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. Recognise how machine learning can help organisations optimise business processes and make effective decisions at scale.
  • LO2. Formulate business decision problems as predictive machine learning problems.
  • LO3. Select relevant machine learning algorithms and tools to solve a range of business prediction and data mining problems.
  • LO4. Evaluate machine learning algorithms and techniques according to their statistical and computational properties.
  • LO5. Extract business insights from large volumes of data using machine learning and data mining methods.
  • LO6. Apply machine learning and data mining techniques using industry-standard computational tools.
  • LO7. Collaborate effectively within data teams.
  • LO8. Communicate data-driven results and insights effectively to a business audience.

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 ? 
Semester 1 2024
Normal day Camperdown/Darlington, Sydney
Semester 2 2024
Normal day Camperdown/Darlington, Sydney
Outline unavailable
Session MoA ?  Location Outline ? 
Semester 1 2020
Normal day Camperdown/Darlington, Sydney
Semester 2 2020
Normal day Camperdown/Darlington, Sydney
Semester 1 2021
Normal day Camperdown/Darlington, Sydney
Semester 1 2021
Normal day Remote
Semester 2 2021
Normal day Camperdown/Darlington, Sydney
Semester 2 2021
Normal day Remote
Semester 1 2022
Normal day Camperdown/Darlington, Sydney
Semester 1 2022
Normal day Remote
Semester 2 2022
Normal day Camperdown/Darlington, Sydney
Semester 2 2022
Normal day Remote
Semester 1 2023
Normal day Camperdown/Darlington, Sydney
Semester 1 2023
Normal day Remote
Semester 2 2023
Normal day Camperdown/Darlington, Sydney

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.