UnitLevel 5Postgraduate

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 2020 in Semester 2 at Clayton. It needs ETC5250.

Credit points
6
Offered in 2020
Semester 2
Clayton
Workload
144 hours
per semester

This is the 2020 handbook entry. See the 2027 entry.

Reviews

No reviews yet

No reviews yet. Be the first to review ETC5555.

Requisites

Before ETC5555

Prerequisites

Pass these before you enrol.

Prohibitions

You can't enrol if you have passed any of these.

After ETC5555

No unit lists ETC5555 as a prerequisite in the 2020 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 2020

Teaching periodCampusMode
Second semesterClaytonOn campus

Learning outcomes

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

  1. 1

    identify and understand the statistical and computational constraints for different types of data problems

  2. 2

    fit the appropriate model(s) for the different data problems

  3. 3

    understand and apply machine learning algorithms to solve new data analysis problems.

Workload and teaching

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.

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 2020, 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.

More details

Credit points
6
Level
5
Study level
Postgraduate
Faculty
Faculty of Business and Economics
Organisational unit
Department of Econometrics and Business Statistics
Type
Coursework
EFTSL
0.125
Student contribution
SCA Band 3
Study abroad
Not available