Data Science Table

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

DATA SCIENCE

Data Science major

A major in Data Science requires 48 credit points from this table including:
(i) 6 credit points of 1000-level core units
(ii) 6 credit points of 1000-level units according to the following rules*:
(a) 6 credit points of selective units OR
(b) 3 credit points of statistics units and 3 credit points of computation units OR
(c) 3 credit points of advanced statistics units and 3 credit points of mathematics units OR
(d) 3 credit points of advanced statistics units and 3 credit points of linear algebra units for students in the Mathematical Sciences program^
(iii) 12 credit points of 2000-level core units
(iv) 6 credit points of 2000-level selective units
(v) 6 credit points of 3000-level core interdisciplinary project units
(vi) 6 credit points of 3000-level methodology units
(vii) 6 credit points of 3000-level methodology or application or interdisciplinary project selective units
*Students not enrolled in the BSc may substitute ECMT1010 or BUSS1020
^If elective space allows, students may substitute DATA1001/1901 for the advanced statistics unit

Data Science minor

A minor in Data Science requires 36 credit points from this table including:
(i) 6 credit points of 1000-level core units
(ii) 6 credit points of 1000-level units according to the following rules*:
(a) 6 credit points of selective units OR
(b) 3 credit points of statistics units and 3 credit points of computations units OR
(c) 3 credit points of advanced statistics units and 3 credit points of calculus and linear algebra units
(iii) 12 credit points of 2000-level core units
(iv) 6 credit points of 2000-level selective units
(v) 6 credit points of 3000-level methodology units

Units of study

The units of study are listed below.

1000-level units of study

Core
DATA1002
Informatics: Data and Computation
6    N INFO1903 OR DATA1902
Semester 2
DATA1902
Informatics: Data and Computation (Advanced)
6    A This unit is intended for students with ATAR at least sufficient for entry to the BSc/BAdvStudies(Advanced) stream, or for those who gained Distinction results or better, in some unit in Data Science, Mathematics, or Computer Science. Students with portfolio of high-quality relevant prior work can also be admitted.
N INFO1903 OR DATA1002

Note: Department permission required for enrolment

Semester 2
Selective
DATA1001
Foundations of Data Science
6    N DATA1901 or MATH1005 or MATH1905 or MATH1015 or MATH1115 or ENVX1001 or ENVX1002 or ECMT1010 or BUSS1020 or STAT1021
Semester 1
Semester 2
DATA1901
Foundations of Data Science (Adv)
6    A An ATAR of 95 or more
N MATH1905 or ECMT1010 or ENVX1002 or BUSS1020 or DATA1001 or MATH1115 or MATH1015
Semester 1
Semester 2
ENVX1002
Introduction to Statistical Methods
6    N ENVX1001 or MATH1005 or MATH1905 or MATH1015 or MATH1115 or DATA1001 or DATA1901 or BUSS1020 or STAT1021 or ECMT1010


Available as a degree core unit only in the Agriculture, Animal and Veterinary Bioscience, and Food and Agribusiness, and Taronga Wildlife Conservation streams
Semester 1
Statistics
MATH1005
Statistical Thinking with Data
3    A HSC Mathematics. Students who have not completed HSC Mathematics (or equivalent) are strongly advised to take the Mathematics Bridging Course (offered in February).
N MATH1015 or MATH1905 or STAT1021 or ECMT1010 or ENVX1001 or ENVX1002 or BUSS1020 or DATA1001 or DATA1901
Intensive January
Semester 1
Semester 2
Computation
MATH1115
Interrogating Data
3    P MATH1005 or MATH1015
N STAT1021 or ENVX1001 or ENVX1002 or BUSS1020 or ECMT1010 or DATA1001 or DATA1901
Intensive January
Semester 1
Semester 2
Advanced Statistics
MATH1905
Statistical Thinking with Data (Advanced)
3    A (HSC Mathematics Extension 2) OR (90 or above in HSC Mathematics Extension 1) or equivalent
N MATH1005 or MATH1015 or STAT1021 or ECMT1010 or ENVX1001 or ENVX1002 or BUSS1020 or DATA1001 or DATA1901

Note: Department permission required for enrolment

Semester 2
Mathematics
MATH1021
Calculus Of One Variable
3    A HSC Mathematics Extension 1 or equivalent.
N MATH1011 or MATH1901 or MATH1906 or ENVX1001 or MATH1001 or MATH1921 or MATH1931
Intensive January
Semester 1
Semester 2
MATH1921
Calculus Of One Variable (Advanced)
3    A (HSC Mathematics Extension 2) OR (Band E4 in HSC Mathematics Extension 1) or equivalent.
N MATH1001 or MATH1011 or MATH1906 or ENVX1001 or MATH1901 or MATH1021 or MATH1931

Note: Department permission required for enrolment

Semester 1
MATH1931
Calculus Of One Variable (SSP)
3    A (HSC Mathematics Extension 2) OR (Band E4 in HSC Mathematics Extension 1) or equivalent.
N MATH1001 or MATH1011 or MATH1901 or ENVX1001 or MATH1906 or MATH1021 or MATH1921

Note: Department permission required for enrolment
Enrolment is by invitation only
Semester 1
MATH1023
Multivariable Calculus and Modelling
3    A Knowledge of complex numbers and methods of differential and integral calculus including integration by partial fractions and integration by parts as for example in MATH1021 or MATH1921 or MATH1931 or HSC Mathematics Extension 2
N MATH1013 or MATH1903 or MATH1907 or MATH1003 or MATH1923 or MATH1933
Intensive January
Semester 1
Semester 2
MATH1923
Multivariable Calculus and Modelling (Adv)
3    A (HSC Mathematics Extension 2) OR (Band E4 in HSC Mathematics Extension 1) or equivalent.
N MATH1003 or MATH1013 or MATH1907 or MATH1903 or MATH1023 or MATH1933

Note: Department permission required for enrolment

Semester 2
MATH1933
Multivariable Calculus and Modelling (SSP)
3    A (HSC Mathematics Extension 2) OR (Band E4 in HSC Mathematics Extension 1) or equivalent.
N MATH1003 or MATH1903 or MATH1013 or MATH1907 or MATH1023 or MATH1923

Note: Department permission required for enrolment
Enrolment is by invitation only.
Semester 2
MATH1002
Linear Algebra
3    A HSC Mathematics or MATH1111. Students who have not completed HSC Mathematics (or equivalent) are strongly advised to take the Mathematics Bridging Course (offered in February).
N MATH1012 or MATH1014 or MATH1902
Intensive January
Semester 1
MATH1902
Linear Algebra (Advanced)
3    A (HSC Mathematics Extension 2) OR (90 or above in HSC Mathematics Extension 1) or equivalent
N MATH1002 or MATH1014

Note: Department permission required for enrolment

Semester 1

2000-level units of study

Core
DATA2001
Data Science: Big Data and Data Diversity
6    P DATA1002 OR DATA1902 OR INFO1110 OR INFO1910 OR INFO1903 OR INFO1103
N DATA2901
Semester 1
DATA2901
Big Data and Data Diversity (Advanced)
6    P DATA1002 OR DATA1902 OR INFO1110 OR INFO1903 OR INFO1103. Students need Distinction or better in one of the prerequisite units.
N DATA2001
Semester 1
DATA2002
Data Analytics: Learning from Data
6    A Basic linear algebra and some coding for example MATH1014 or MATH1002 or MATH1902 and DATA1001 or DATA1901
P [DATA1001 or ENVX1001 or ENVX1002] or [MATH10X5 and MATH1115] or [MATH10X5 and STAT2X11] or [MATH1905 and MATH1XXX (except MATH1XX5)] or [BUSS1020 or ECMT1010 or STAT1021]
N STAT2012 or STAT2912 or DATA2902
Semester 2
DATA2902
Data Analytics: Learning from Data (Adv)
6    A Basic linear algebra and some coding for example MATH1014 or MATH1002 or MATH1902 and DATA1001 or DATA1901
P A mark of 65 or above in any of the following (DATA1001 or DATA1901 or ENVX1001 or ENVX1002) or (MATH10X5 and MATH1115) or (MATH10X5 and STAT2011) or STAT2911 or (MATH1905 and MATH1XXX [except MATH1XX5]) or (BUSS1020 or ECMT1010 or STAT1021)
N STAT2012 or STAT2912 or DATA2002
Semester 2
Selective
COMP2123
Data Structures and Algorithms
6    P INFO1110 OR INFO1910 OR INFO1113 OR DATA1002 OR DATA1902 OR INFO1103 OR INFO1903
N INFO1105 OR INFO1905 OR COMP2823
Semester 1
COMP2823
Data Structures and Algorithms (Adv)
6    P INFO1110 OR INFO1910 OR INFO1113 OR DATA1002 OR DATA1902 OR INFO1103 OR INFO1903
N INFO1105 OR INFO1905 OR COMP2123
Semester 1
COSC2002
Computational Modelling
6    A HSC Mathematics; DATA1002, or equivalent programming experience, ideally in Python.
N COSC1003 or COSC1903 or COSC2902
Semester 1
COSC2902
Computational Modelling (Advanced)
6    A HSC Mathematics; DATA1002, or equivalent programming experience, ideally in Python.
P 48 credit points of 1000 level units with an average of 65
N COSC1003 or COSC1903 or COSC2002

Note: Department permission required for enrolment

Semester 1
STAT2011
Probability and Estimation Theory
6    P (MATH1X21 or MATH1931 or MATH1X01 or MATH1906 or MATH1011) and (DATA1X01 or MATH10X5 or MATH1905 or STAT1021 or ECMT1010 or BUSS1020)
N STAT2911
Semester 1
STAT2911
Probability and Statistical Models (Adv)
6    P (MATH1X21 or MATH1931 or MATH1X01 or MATH1906 or MATH1011) and a mark of 65 or greater in (DATA1X01 or MATH10X5 or MATH1905 or STAT1021 or ECMT1010 or BUSS1020)
N STAT2011
Semester 1
QBUS2830
Actuarial Data Analytics

This unit of study is not available in 2020

6    A BUSS1020 or ECMT1010 or ENVX1001 or ENVX1002 or ((MATH1005 or MATH1015) and MATH1115) or 6 credit points in MATH 1000-level units including MATH1905.
P QBUS2810 or DATA2002 or ECMT2110
Semester 1
GEGE2001
Genetics and Genomics
6    A Mendelian genetics; mechanisms of evolution; molecular and chromosomal bases of inheritance; and gene regulation and expression.
N GENE2002 or MBLG2972 or GEGE2901 or MBLG2072
Semester 1
Semester 2
GEGE2901
Genetics and Genomics (Advanced)
6    A Mendelian genetics, mechanisms of evolution, molecular and chromosomal bases of inheritance, and gene regulation and expression.
P Annual average mark of at least 70
N GENE2002 or MBLG2072 or GEGE2001 or MBLG2972
Semester 1
Semester 2
QBIO2001
Molecular Systems Biology
6    A Basic concepts in metabolism; protein synthesis; gene regulation; quantitative and statistical skills
Semester 1

3000-level units of study

Core interdisciplinary project
DATA3888
Data Science Capstone
6    P DATA2001 or DATA2901 or DATA2002 or DATA2902 or STAT2912 or STAT2012
Semester 1
Methodology
DATA3404
Data Science Platforms
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
Semester 1
DATA3406
Human-in-the-Loop Data Analytics
6    A Basic statistics, database management, and programming.
Semester 2
COMP3308
Introduction to Artificial Intelligence
6    A Algorithms. Programming skills (e.g. Java, Python, C, C++, Matlab)
N COMP3608
Semester 1
COMP3608
Introduction to Artificial Intelligence (Adv)
6    A Algorithms. Programming skills (e.g. Java, Python, C, C++, Matlab)
P 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).
Semester 1
COMP3027
Algorithm Design
6    A MATH1004 OR MATH1904 OR MATH1064
P COMP2123 OR COMP2823 OR INFO1105 OR INFO1905
N COMP2007 OR COMP2907 OR COMP3927
Semester 1
COMP3927
Algorithm Design (Adv)
6    A MATH1004 OR MATH1904 OR MATH1064
P COMP2123 OR COMP2823 OR INFO1105 OR INFO1905
N COMP2007 OR COMP2907 OR COMP3027
Semester 1
STAT3021
Stochastic Processes
6    P STAT2X11 and (MATH1003 or MATH1903 or MATH1907 or MATH1023 or MATH1923 or MATH1933)
N STAT3911 or STAT3011
Semester 1
STAT3022
Applied Linear Models
6    P STAT2X11 and (DATA2X02 or STAT2X12)
N STAT3912 or STAT3012 or STAT3922
Semester 1
STAT3922
Applied Linear Models (Advanced)
6    P STAT2X11 and [a mark of 65 or greater in (STAT2X12 or DATA2X02)]
N STAT3912 or STAT3012 or STAT3022
Semester 1
STAT3023
Statistical Inference
6    A DATA2X02 or STAT2X12
P STAT2X11
N STAT3913 or STAT3013 or STAT3923
Semester 2
STAT3923
Statistical Inference (Advanced)
6    P STAT2X11 and a mark of 65 or greater in (DATA2X02 or STAT2X12)
N STAT3913 or STAT3013 or STAT3023
Semester 2
STAT4025
Time Series
6    P STAT2X11 and (MATH1X03 or MATH1907 or MATH1X23 or MATH1933)
N STAT3925
Semester 1
STAT4026
Statistical Consulting
6    P At least 12cp from STAT2X11 or STAT2X12 or DATA2X02 or STAT3XXX
N STAT3926
Semester 1
Application
ENVX3001
Environmental GIS
6    P 6cp from (ENVI1003 or AGEN1002) or 6cp from GEOS1XXX or 6cp from BIOL1XXX or GEOS2X11
Semester 2
ENVX3002
Statistics in the Natural Sciences
6    P ENVX2001 or STAT2X12 or BIOL2X22 or DATA2X02 or QBIO2001
Semester 1
AMED3002
Interrogating Biomedical and Health Data
6    A Exploratory data analysis, sampling, simple linear regression, t-tests, confidence intervals and chi-squared goodness of fit tests, familiar with basic coding, basic linear algebra.
Semester 1
QBUS3810
Actuarial Risk Analytics

This unit of study is not available in 2020

6    P QBUS2810 or DATA2002 or ECMT2110
N ECMT3180
Semester 1
GEGE3004
Applied Genomics
6    A Genetics at 2000 level, Biology at 1000 level, algebra
P 6cp of (GEGE2X01 or QBIO2XXX or DATA2X01 or GENE2XXX or MBLG2X72 or ENVX2001 or DATA2X02)
N ANSC3107


This unit must be taken by all students in the Genetics and Genomics major.
Semester 2
BCMB3004
Beyond The Genome
6    A Intermediate protein chemistry and biochemistry concepts
P 12 credit points from (AMED3001 or BCHM2X71 or BCHM2X72 or BCHM3XXX or BCMB2X01 or BCMB2X02 or BCMB3XXX or BIOL2X29 or BMED2401 or BMED2405 or GEGE2X01 or MBLG2X01 or MEDS2002 or MEDS2003 or PCOL2X21 or QBIO2001)
N BCHM3X81 or BCMB3002
Semester 2
BCMB3904
Beyond The Genome (Advanced)
6    A Students should understand basic concepts in human, mammalian, plant and/or prokaryotic biology. Students should have a basic understanding of the 'genome' and of the central dogma of molecular biology (gene transcription and protein translation). Additional knowledge of basic chemistry and protein biochemistry will be helpful.
P An average mark of 75 or above in 12 credit points from (AMED3001 or BCHM2X71 or BCHM2X72 or BCHM3XXX or BCMB2X01 or BCMB2X02 or BCMB3XXX or BIOL2X29 or BMED2401 or BMED2405 or GEGE2X01 or MBLG2X01 or MEDS2002 or MEDS2003 or PCOL2X21 or QBIO2001)
N BCHM3X92 or BCMB3004
Semester 2
Selective Interdisciplinary Project
SCPU3001
Science Interdisciplinary Project
6    P Completion of 2000-level units required for at least one Science major.
Intensive February
Intensive July
Semester 1
Semester 2
STAT3888
Statistical Machine Learning
6    A STAT3012 or STAT3912 or STAT3022 or STAT3922
P STAT2X11 and (DATA2X02 or STAT2X12)
N STAT3914 or STAT3014
Semester 2