Course structure: Master of Applied Data Analytics (MC-APPDA) — The University of Melbourne Handbook

You’re currently viewing the 2024 version of this course

Course structure

All students must complete:

25 credit points of core subjects

50 credit points of elective subjects

25 credit points of capstone subjects

Subject options

Compulsory subjects

Code	Name	Study period	Credit Points
MAST90130	Critical Thinking with Analytics	Term 1 (Online) Term 3 (Online)	12.5
MGMT90248	Analytics and Society	Term 2 (Online) Term 4 (Online)	12.5

Elective subjects

Code	Name	Study period	Credit Points
ABPL90407	Representing Spatial Information	Term 1 (Online)	12.5
ABPL90408	Spatial Analytics	Term 3 (Online)	12.5
MGMT90239	Business Analytics for Decision Making	Term 1 (Online) Term 3 (Online)	12.5
MAST90131	Measurement Analytics	Term 3 (Online)	12.5
COMP90076	Social Analytics	Term 1 (Online)	12.5
MAST90135	Foundations of Analytics	Term 4 (Online)	12.5
POPH90295	Designing Analytics Investigations	Not available in 2024	12.5
MAST90134	Advanced Elements of Analytics	Not available in 2024	12.5
POPH90144	Regression Methods in Health Research	July (Dual-Delivery - Parkville)	12.5
POPH90014	Epidemiology 1	Semester 1 (Dual-Delivery - Parkville) Semester 2 (Dual-Delivery - Parkville)	12.5
PSYC90109	Introduction to Experience Sampling	No longer available
GEOM90007	Information Visualisation	Semester 2 (Online)	12.5

Code	Name	Study period	Credit Points
INFO90001	Digital Health and Informatics Methods	Semester 1 (Online) Semester 2 (Online)	12.5

Casptone subjects

Code	Name	Study period	Credit Points
MGMT90250	Applied Analytics Capstone Part 1	Term 3 (Online)	12.5
MGMT90251	Applied Analytics Capstone Part 2	Term 4 (Online)	12.5

Last updated: 8 March 2026