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Unit of study_

MKTG6010: Machine Learning in Marketing

2024 unit information

With fast growth of the modern digital economy, multi-quintillion bytes of data is generated every day. This provides an enormous opportunity and a significant challenge for marketers to extract marketing insights because of not only the size of the data, but also the structure of the data. A growing proportion of the data is unstructured, such as customer emails and texts, mobile data, social media UGCs, C2C data on two-sided platforms in the sharing economy. Traditional marketing research methods cannot be used to solve these problems. This unit introduces state of the art machine learning methods to help marketers extract consumers insights from big data including structured and unstructured data and make better informed business decisions.

Unit details and rules

Managing faculty or University school:

Marketing

Code MKTG6010
Academic unit Marketing
Credit points 6
Prerequisites:
? 
BUSS6002 OR QBUS5011
Corequisites:
? 
None
Prohibitions:
? 
None
Assumed knowledge:
? 
None

At the completion of this unit, you should be able to:

  • LO1. Apply machine learning methods commonly used in marketing and evaluate the advantages and disadvantages of those methods
  • LO2. Identify the machine learning models required to analyze practical problems in marketing
  • LO3. Apply machine learning to extract insights from big data for better decision making
  • LO4. Apply the required analytical techniques across marketing units

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

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.