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Computational Data Science

Unit of study table

This page was first published on 13 November 2025 and was last amended on 19 January 2026.
View details of the changes below.

Computational Data Science major

Achievement of a major in Computational Data Science requires 48 credit points from this table including:
(i) 12 credit points of 1000-level core units
(ii) 18 credit points of 2000-level core units
(iii) 6 credit points of 3000-level core units
(iv) 12 credit points of 3000-level selective units

Computational Data Science minor

Achievement of a minor in Computational Data Science requires 36 credit points from this table including:
(i) 12 credit points of 1000-level core units.
(ii) 18 credit points of 2000-level core units.
(iii) 6 credit points of 3000-level selective units.
Unit of study
Credit points
A: Assumed knowledge P: Prerequisites
C: Corequisites N: Prohibition

1000-level units of study

Core units

DATA1001
Foundations of Data Science

6

A Year 10 mathematics or equivalent
N DATA1901 or MATH1005 or MATH1905 or MATH1015 or MATH1115 or ENVX1002 or ECMT1010 or BUSS1020

DATA1901
Foundations of Data Science (Adv)

6

A Year 10 Mathematics or equivalent; An ATAR of 95 or more
N MATH1005 or MATH1905 or ENVX1002 or ECMT1010 or BUSS1020 or DATA1001 or MATH1115 or MATH1015

INFO1110
Introduction to Programming

6

N INFO1910 or INFO1103 or INFO1903 or INFO1105 or INFO1905 or ENGG1810

INFO1910
Introduction to Programming (Advanced)

6

A ATAR sufficient to enter Dalyell program, or passing an online programming knowledge test, which will be administered during the O-week prior to the commencement of the semester
N INFO1110 or INFO1103 or INFO1903 or INFO1105 or INFO1905 or ENGG1810

2000-level units of study

Core units

COMP2123
Data Structures and Algorithms

6

A Discrete mathematics and probability (e.g. MATH1064 or equivalent)
P INFO1110 or INFO1910 or INFO1113 or DATA1002 or DATA1902 or ENGG1810
N INFO1105 or INFO1905 or COMP2823

COMP2823
Data Structures and Algorithms (Adv)

6

A Discrete mathematics and probability (e.g. MATH1064 or equivalent)
P Distinction level results in (INFO1110 or INFO1910 or INFO1113 or DATA1002 or DATA1902 or ENGG1810)
N INFO1105 or INFO1905 or COMP2123

DATA2001
Data Science, Big Data and Data Variety

6

P DATA1002 or DATA1902 or INFO1110 or INFO1910 or INFO1903 or INFO1103 or ENGG1810
N DATA2901

DATA2901
Big Data and Data Diversity (Advanced)

6

P 75% or above from (DATA1002 or DATA1902 or INFO1110 or INFO1910 or INFO1903 or INFO1103 or ENGG1810)
N DATA2001

DATA2002
Data Analytics: Learning from Data

6

A Successful completion of a first-year or second-year unit in statistics or data science including a substantial coding component. The content from STAT2X11 will help but is not considered essential. Students who are not comfortable using the R software for statistical analysis should familiarise themselves before attempting the unit, e.g. taking OLET1632: Shark Bites and Other Data Stories
P DATA1X01 or ENVX1002 or BUSS1020 or ECMT1010 or MATH1062 or MATH1962 or MATH1972 or [MATH1X05 and (MATH1001 or MATH1002 or MATH1003 or MATH1004 or MATH1021 or MATH1023 or MATH1115 or MATH19XX)]
N STAT2012 or STAT2912 or DATA2902

DATA2902
Data Analytics: Learning from Data (Adv)

6

A Successful completion of a first-year or second-year unit in statistics or data science including a substantial coding component. The content from STAT2X11 will help but is not considered essential. Students who are not comfortable using the R software for statistical analysis should familiarise themselves before attempting the unit, e.g. taking OLET1632: Shark Bites and Other Data Stories
P A mark of 65 or greater in (DATA1X01 or ENVX1002 or BUSS1020 or ECMT1010 or MATH1062 or MATH1962 or MATH1972 or [MATH1X05 and (MATH1001 or MATH1002 or MATH1003 or MATH1004 or MATH1021 or MATH1023 or MATH1115 or MATH19XX)])
N STAT2012 or STAT2912 or DATA2002

3000-level units of study

Core units

DATA3888
Data Science Capstone

6

P DATA2001 or DATA2901 or DATA2002 or DATA2902 or STAT2912 or STAT2012

Selective units

COMP3027
Algorithm Design

6

A Discrete mathematics and probability (e.g. MATH1064 or equivalent)
P COMP2123 or COMP2823
N COMP2007 or COMP2907 or COMP3927

COMP3927
Algorithm Design (Adv)

6

A Discrete mathematics and probability (e.g. MATH1064 or equivalent)
P Distinction level results in COMP2123 or COMP2823
N COMP2007 or COMP2907 or COMP3027

COMP3308
Introduction to Artificial Intelligence

6

A Data structures and algorithms as covered in COMP2123 or COMP2823.
P INFO1110 or INFO1910 or ENGG1801 or ENGG1810 or DATA1002 or DATA1902
N COMP3608

COMP3608
Introduction to Artificial Intelligence (Adv)

6

A Data structures and algorithms as covered in COMP2123 or COMP2823.
P (INFO1110 or INFO1910 or ENGG1810 or DATA1002 or DATA1902) and distinction-level results in at least one 2000-level COMP or MATH or SOFT unit
N COMP3308
COMP3308 and COMP3608 share the same lectures, but have different tutorials and assessment (the same type but more challenging).

DATA3404
Scalable Data Management

6

A This unit of study assumes that students have previous knowledge of database structures and of SQL. The prerequisite material is covered in DATA2001 or ISYS2120. Familiarity with a programming language (e.g. Java or C) is also expected
P DATA2001 or DATA2901 or ISYS2120 or INFO2120 or INFO2820
N INFO3504 or INFO3404

DATA3406
Human-in-the-Loop Data Analytics

6

A Basic statistics, database management, and programming
P (DATA2001 or DATA2901) and (DATA2002 or DATA2902)

Post-publication amendments

Date Original publication Post-publication amendment
19/01/2026

COMP3530 was published and available for selection from:

3000-level units of study.

COMP3530 removed.