UnitLevel 3Undergraduate

ETX3250 Predictive analytics and machine learning

Faculty of Business and Economics

ETX3250 Predictive analytics and machine learning is a level 3, 6-credit-point, undergraduate unit from the Faculty of Business and Economics, offered in 2025 in Semester 1 at Caulfield. It needs ETC1010, ETX2250, ETC2420, ETF2020 or ETW2001 and unlocks 2 units.

Credit points
6
Offered in 2025
Semester 1
Caulfield
Assessment
Exam 50%
and 1 other task
Workload
144 hours
per semester

This is the 2025 handbook entry. See the 2027 entry.

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Requisites

Enrolment rules

To be successful in this unit, background knowledge and application of maths is required at the equivalent of VCE Year 12 level.  You may have satisfied this by completing relevant prerequisite unit/s, or you have covered relevant topics in your final years of secondary study.  You should self-assess your maths competency prior to enrolling in this unit.

Equivalent units

The same content under another code. Only one of them counts.

Overview

Many problems in business including sales and inventory forecasting, credit scoring, recommender systems in online commerce and fraud detection use advanced tools for data analytics. This unit covers some of the most popular tools that may include tree-based methods, boosting, bagging, support vector machines, neural networks and deep learning. The algorithmic details of each method, their implementation using popular software tools (such as R) and their application to real business problems will all be covered.

Offerings in 2025

Teaching periodCampusMode
First semesterCaulfieldBlended

Assessment

  • Within semester assessment
    50%
  • Examination
    50%

Learning outcomes

When you finish this unit, you should be able to:

  1. 1

    understand different techniques used in business analytics and to be able to compare these from a statistical and computational point of view

  2. 2

    frame problems in finance, marketing, economics and related areas so that they can be solved by modern tools in business analytics

  3. 3

    implement machine learning methods in a modern software environment (for example, R) with potentially large datasets

  4. 4

    explain and interpret the analyses undertaken in a clear and effective manner and be aware of the limitations of these analyses.

Workload and teaching

  • Tutorials12 hours
  • Seminars24 hours
  • Workshops12 hours
  • Teaching approachActive learning

Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled learning activities and independent study. Independent study may include associated readings, assessment and preparation for scheduled activities. You are expected to complete all pre-class activities prior to your scheduled class, and post-class activities should be completed after your scheduled class. Learning activities may include a combination of teacher directed, peer directed and online engagement activities.

This unit engages you in actively applying your knowledge, skills and attributes in interactive, collaborative and reflective activities.

Learning resources

Technology resources

There may be an additional cost associated with purchasing a physical and/or virtual calculator. Specific details will be provided in the Learning Management System by commencement of Orientation week.

Where it fits

ETX3250 is part of 2 areas of study in the 2025 handbook.

Contacts

Chief Examiners
Dr Ruben Loaiza Maya

Common questions

What are the prerequisites for ETX3250?

You need ETC1010, ETX2250, ETC2420, ETF2020 or ETW2001 before you enrol. Enrolment rules also apply.

What can I take after ETX3250?

ETX3250 is a prerequisite or corequisite for 2 units, including ETC3555 and ETC5555.

When is ETX3250 offered?

In 2025, ETX3250 runs in Semester 1 at Caulfield.

How much work is ETX3250?

The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.

Does ETX3250 have an exam?

Yes. The exam is worth 50% of the final mark, alongside 1 other task.

Which majors and minors include ETX3250?

ETX3250 is part of Business analytics and statistics.

More details

Credit points
6
Level
3
Study level
Undergraduate
Faculty
Faculty of Business and Economics
Organisational unit
Department of Econometrics and Business Statistics
Type
Coursework
EFTSL
0.125
Student contribution
SCA Band 1
Study abroad
Not available
Handbook years
2021202220232024202520262027