ETC5555 Statistical machine learning
Faculty of Business and Economics
ETC5555 Statistical machine learning is a level 5, 6-credit-point, postgraduate unit from the Faculty of Business and Economics, offered in 2022 in Semester 2 at Clayton. It needs ETC5250.
- Credit points
- 6
- Offered in 2022
- Semester 2
- Clayton
- Assessment
- Exam 60%
- and 1 other task
- Workload
- 144 hours
- per semester
This is the 2022 handbook entry. See the 2027 entry.
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Requisites
Before ETC5555
Prohibitions
You can't enrol if you have passed any of these.
Prerequisites
Pass these before you enrol.
After ETC5555
No unit lists ETC5555 as a prerequisite in the 2022 handbook.
Equivalent units
The same content under another code. Only one of them counts.
Overview
This unit covers the methods and practice of statistical machine learning for modern data analysis problems. Topics covered will include recommender systems, social networks, text mining, matrix decomposition and completion, and sparse multivariate methods. All computing will be conducted using the R programming language.
Offerings in 2022
| Teaching period | Campus | Mode |
|---|---|---|
| Second semester | Clayton | On campus |
Assessment
- Within semester assessment40%
- ExaminationThreshold hurdle60%
Learning outcomes
When you finish this unit, you should be able to:
- 1
identify and understand the statistical and computational constraints for different types of data problems
- 2
fit the appropriate model(s) for the different data problems
- 3
understand and apply machine learning algorithms to solve new data analysis problems.
Workload and teaching
- Tutorials18 hours
- Lectures24 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. 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.
This unit engages you in actively applying your knowledge, skills and attributes in interactive, collaborative and reflective activities.
Contacts
- Chief Examiners
- Dr Klaus Ackermann
Common questions
What are the prerequisites for ETC5555?
You need ETC5250 before you enrol.
When is ETC5555 offered?
In 2022, ETC5555 runs in Semester 2 at Clayton.
How much work is ETC5555?
The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.
Does ETC5555 have an exam?
Yes. The exam is worth 60% of the final mark, alongside 1 other task.