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Master of Data Science

Online unit of study table

This page was first published on 21 November 2022 and was last amended on 30 January 2023.
View details of the changes below.

Master of Data Science

To qualify for the award of the Master of Data Science, a candidate must complete 72 credit points, comprising:
For the Professional Pathway:
(i) 30 credit points of Core units of study consisting of 18 credit points of Data Science Core units of study and 12 credit points of Professional Core units of study; and
(ii) 12 credit points of Capstone Project units of study taken as two 6 credit point units over two semesters; and 
(iii) a minimum of 18 credit points of Specialisation units of study or Data Science Specialist units of study
(iv) a maximum of 12 credit points of Elective units of study.

Graduate Diploma in Data Science

To qualify for the award of the Graduate Diploma in Data Science, a candidate must complete 48 credit points of units of study including
(i) A minimum of 12 credit points of Data Science Core units of study; and
(ii) A minimum of 6 credit points of Professional Core units of study; and
(iii) A minimum of 12 credit points of Data Science Specialist units of study; and
(iv) A maximum of 12 credit points of Elective units of study.

Graduate Certificate in Data Science

To qualify for the award of the Graduate Certificate in Data Science candidates must complete 24 credit points of units of study including:
(i) 12 credit points of Data Science Core units of study consisting of OCMP5310 and OSTA5003; and
(ii) 12 credit points of Data Science Specialist units of study.

 

Unit of study Credit points A: Assumed knowledge P: Prerequisites
C: Corequisites N: Prohibition

Core units of study

Data Science Core units of study
OCMP5048
Visual Analytics 
6 A Experience with data structures and algorithms as covered in COMP9123 or COMP9103 or COMP9003 or COMP2123 or COMP2823 or INFO1105 or INFO1905 (or equivalent UoS from different institutions)
N COMP5048 or COMP4448
OCMP5310
Principles of Data Science
6 A Good understanding of relational data model and database technologies as covered in ISYS2120 or COMP9120 (or equivalent UoS from different institutions)
N COMP5310 or INFO3406
OSTA5003
Computational Statistical Methods
6 A STAT5002 or equivalent introductory statistics course with a statistical computing component
Professional Core units of study
OINF5990
Professional Practice in IT
6 A Students enrolled in INFO5990 are assumed to have previously completed a Bachelor's degree in some area of IT, or have completed a Graduate Diploma in some area of IT, or have many years experience as a practising IT professional
N INFO5990
OINF5992
Understanding IT Innovations
6 N INFO5992 or PMGT5875

Data Science Specialist units of study

OCMP5318
Machine Learning and Data mining 
6 A Experience with programming and data structures as covered in COMP2123 or COMP2823 or COMP9123 (or equivalent unit of study from different institutions)
N COMP5318 or COMP4318 
OCMP5328
Advanced Machine Learning

6 C OCMP5318 or COMP5318 or COMP4318 or COMP3308 or COMP3608
N COMP5328 or COMP4328
OCMP5329
Deep Learning

6 A OCMP5318 or COMP5318 or COMP4318
N COMP5329 or COMP4329
OCMP5338
Advanced Data Models

6 A This unit of study assumes foundational knowledge of relational database systems as taught in COMP5138/COMP9120 (Database Management Systems) or INFO2120/INFO2820/ISYS2120 (Database Systems 1)
N COMP5338 or COMP4338
OCMP5339
Data Engineering 

6 A Proficiency in programming, especially Python, and in database querying with SQL; basic Unix scripting
P COMP5310 or OCMP5310
N COMP5329 or COMP4329

Elective units of study

OCMP5426
Parallel and Distributed Computing

6 A Experience with algorithm design and software development as covered in (COMP2017 or COMP9017) and COMP3027 or COMP3927 (or equivalent UoS from different institutions)
N COMP5426 or COMP4426

Capstone Project units of study 

Data Science Capstone A
6 Unit under development. Not available for enrolment in 2023.
Data Science Capstone B
6 Unit under development. Not available for enrolment in 2023.

Specialisations for the Master of Data Science

A Specialisation requires the completion of 18 credit points of Specialisation Core units of study as defined in the tables below.
Data Engineering specialisation
Specialisation Core units of study
OCMP5338
Advanced Data Models

6 A This unit of study assumes foundational knowledge of relational database systems as taught in COMP5138/COMP9120 (Database Management Systems) or INFO2120/INFO2820/ISYS2120 (Database Systems 1)
N COMP5338 or COMP4338
OCMP5349
Cloud Computing

6 A Basic knowledge of computer networks as covered in INFO1112 or COMP9201 or COMP9601 (or equivalent UoS from different institutions)
N COMP5349 or COMP4349
OCMP5339
Data Engineering

6 A Proficiency in programming, especially Python, and in database querying with SQL; basic Unix scripting
P COMP5310 or OCMP5310
N COMP5329 or COMP4329
Machine Learning specialisation
Specialisation Core units of study
OCMP5318
Machine Learning and Data mining

6 A Experience with programming and data structures as covered in COMP2123 or COMP2823 or COMP9123 (or equivalent unit of study from different institutions)
N COMP5318 or COMP4318
OCMP5328
Advanced Machine Learning

6 C OCMP5318 or COMP5318 or COMP4318 or COMP3308 or COMP3608
N COMP5328 or COMP4328
OCMP5329
Deep Learning

6 A OCMP5318 or COMP5318 or COMP4318
N COMP5329 or COMP4329
Unspecified specialisation
Unspecified Specialisation requires the completion of 18 credit points from the Data Science Specialist units of study table.

Post-publication amendments

Date Original publication Post-publication amendment
30/01/2023 Prerequisites (P) for OINF5992 published as:
P 24 credit points of units at 5000-level or above
Prerequisites (P) for OINF5992 removed: