Overview

This unit aims to develop and enhance students’ conceptual and practical understanding of Predictive Analytics as an advanced topic in business analytics. Using an appropriate predictive model on select datasets, an organisation would be able to identify the likelihood of future outcomes based on historical and current data. The business foresight based on this analytics is instrumental in strategic decision making processes of the organisation. Students will have an opportunity to immerse themselves in problem-solving activities requiring lateral and critical thinking by exploring structured and unstructured data, considering and applying the appropriate Predictive Analytics techniques. .

Requisites

Prerequisites
INF70008 Business Analytics and Visualisation

Rule
Admission into a Masters level course from the School of Business Law and Entrepreneurship

AND
INF70008 Business Analytics and Visualisation
OR
Enrolment in Master of Information Technology (Professional Computing)

AND
INF60012 Cloud Enterprise Systems and Analytics
OR
Enrolment in Master of Information Technology
AND
INF60007 Business Information Systems

Teaching Periods
Location
Start and end dates
Last self-enrolment date
Census date
Last withdraw without fail date
Results released date
Semester 2
Location
Hawthorn
Start and end dates
29-July-2024
27-October-2024
Last self-enrolment date
11-August-2024
Census date
31-August-2024
Last withdraw without fail date
13-September-2024
Results released date
03-December-2024

Learning outcomes

Students who successfully complete this unit will be able to:

  • Demonstrate the ability to systematically identify and review strategic opportunities through the application of Predictive Analytics on organisational datasets
  • Apply problem solving and decision-making techniques in order to evaluate the requirements for information and data/datasets enabling an effective use of Predictive Analytics tools and techniques
  • Critically analyse appropriate datasets using Predictive Analytics tools and techniques to generate business foresights
  • 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
Literature ReviewIndividual 20 - 30% 
ProjectGroup 30 - 50% 2,3,4 
ReportIndividual 30 - 40% 1,3 

Content

•    The strategic importance of Predictive Analytics for a contemporary organisation
•    The role of big data and analytics in strategic decision making and identifying business opportunities
•    Predictive modelling: Trending and Forecasting
•    Use cases of Predictive Analytics
•    The concepts of Machine Learning, supervised learning, unsupervised learning, reinforcement learning
 

Study resources

Reading materials

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