Overview

This unit develops and enhances students’ conceptual and practical understanding of artificial intelligence (and in particular machine learning) in various business contexts where artificial intelligence has emerged to play a crucial role. Students learn about fundamental concepts, key techniques and popular tools in artificial intelligence and learn how it is influencing various businesses and industries. Students also acquire the ability to apply artificial intelligence techniques and tools to resolve issues and problems arising in different business contexts.

Teaching periods
Location
Start and end dates
Last self-enrolment date
Census date
Last withdraw without fail date
Results released date
Semester 1
Location
Hawthorn
Start and end dates
03-March-2025
01-June-2025
Last self-enrolment date
16-March-2025
Census date
31-March-2025
Last withdraw without fail date
24-April-2025
Results released date
08-July-2025
Semester 2
Location
Hawthorn
Start and end dates
04-August-2025
02-November-2025
Last self-enrolment date
17-August-2025
Census date
31-August-2025
Last withdraw without fail date
19-September-2025
Results released date
09-December-2025

Learning outcomes

Students who successfully complete this unit will be able to:

  • Demonstrate advanced knowledge of fundamental concepts, key techniques and popular tools in machine learning
  • Critically evaluate the roles of machine learning in various business contexts
  • Critically analyse, evaluate and apply appropriate machine learning techniques and tools to solve various business problems
  • Communicate effectively as a professional and function as an effective leader or member of a team

Teaching methods

Hawthorn

Type Hours per week Number of weeks Total (number of hours)
On-campus
Class		2.00 12 weeks 24
Online
Lecture		1.00 12 weeks 12
Unspecified Activities
Independent Learning		9.50 12 weeks 114
TOTAL150

Assessment

Type Task Weighting ULO's
AssignmentIndividual 20 - 30% 1,2,3 
Case PresentationGroup 40 - 60% 1,2,3,4 
ReportIndividual 20 - 30% 1,2 

Content

  • Foundations of artificial intelligence (especially machine learning)
  • Machine learning applications in different business areas
  • Key machine learning techniques: supervised, unsupervised and semi-supervised
  • Popular machine learning tools and computing platforms
  • Applications of machine learning to different business areas such as financial services, supply chain management, healthcare and telecommunication

Study resources

Reading materials

A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.