ETC5250 Introduction to machine learning
Faculty of Business and Economics
ETC5250 Introduction to machine learning is a level 5, 6-credit-point, postgraduate unit from the Faculty of Business and Economics, offered in 2021 in Semester 1 at Clayton. It needs ETC2420 or ETC5242 and unlocks 1 unit.
- Credit points
- 6
- Offered in 2021
- Semester 1
- Clayton
- Assessment
- Exam 60%
- and 1 other task
- Workload
- 144 hours
- per semester
This is the 2021 handbook entry. See the 2027 entry.
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Requisites
Before ETC5250
Prerequisites
Pass these before you enrol.
Prohibitions
You can't enrol if you have passed any of these.
After ETC5250
1 unit list ETC5250 as a prerequisite or corequisite.
Equivalent units
The same content under another code. Only one of them counts.
Overview
Business analytics involves uncovering the hidden information in masses of business data using statistical models and algorithms. In this unit, some of the most widely used prediction and classification models will be covered. A suitable software environment for business analytics will be used, and tools for handling large data sets will be introduced.
You will explore the trade-off and distinction between prediction, explanation and interpretation using statistical models. Topics to be covered include numerical optimisation; Monte Carlo simulation; resampling methods such as the bootstrap, cross-validation, and bagging; nonlinear and nonparametric methods such as regression splines, trees and support vector machines; principal components analysis and clustering.
Offerings in 2021
| Teaching period | Campus | Mode |
|---|---|---|
| First semester | Clayton | On campus |
Assessment
- Within semester assessment40%
- Examination60%
Learning outcomes
When you finish this unit, you should be able to:
- 1
understand the terminology related to data mining
- 2
use the computer to fit models for data mining
- 3
measure the uncertainty of a prediction or classification using resampling methods
- 4
effectively apply business analytic tools.
Workload and teaching
- Lectures24 hours
- Laboratories18 hours
- Teaching approachProblem-based 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. The unit requires on average three/four hours of scheduled activities per week. Scheduled activities may include a combination of teacher directed learning, peer directed learning and online engagement.
Learning resources
Required resources
The textbook is available online. Lectures and reading material for the unit will also be available online.
Contacts
- Chief Examiners
- Professor Dianne Cook
Common questions
What can I take after ETC5250?
ETC5250 is a prerequisite or corequisite for 1 unit, including ETC5555.
When is ETC5250 offered?
In 2021, ETC5250 runs in Semester 1 at Clayton.
How much work is ETC5250?
The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.
Does ETC5250 have an exam?
Yes. The exam is worth 60% of the final mark, alongside 1 other task.