Predictive Analytics
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
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
27-October-2024
02-November-2025
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 |
| TOTAL | 150 |
Assessment
| Type | Task | Weighting | ULO's |
|---|---|---|---|
| Literature Review | Individual | 20 - 30% | 1 |
| Project | Group | 30 - 50% | 2,3,4 |
| Report | Individual | 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.