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Data Science

Unit of study table (Table S)

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

 

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

1000-level units of study

Core
DATA1002
Informatics: Data and Computation
6    INFO1903 OR DATA1902
DATA1902
Informatics: Data and Computation (Advanced)
6    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
INFO1903 OR DATA1002
Selective
DATA1001
Foundations of Data Science
6    DATA1901 or MATH1005 or MATH1905 or MATH1015 or MATH1115 or ENVX1001 or ENVX1002 or ECMT1010 or BUSS1020 or STAT1021
DATA1901
Foundations of Data Science (Adv)
6    An ATAR of 95 or more
MATH1005 or MATH1905 or ECMT1010 or ENVX1001 or ENVX1002 or BUSS1020 or DATA1001 or MATH1115 or MATH1015 or STAT1021
ENVX1002
Introduction to Statistical Methods
6    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
Statistics
MATH1005
Statistical Thinking with Data
3    HSC Mathematics Advanced or equivalent
MATH1015 or MATH1905 or STAT1021 or ECMT1010 or ENVX1001 or ENVX1002 or BUSS1020 or DATA1001 or DATA1901
Computation
MATH1115
Interrogating Data
3    MATH1005 or MATH1015
STAT1021 or ENVX1001 or ENVX1002 or BUSS1020 or ECMT1010 or DATA1001 or DATA1901
Advanced Statistics
MATH1905
Statistical Thinking with Data (Advanced)
3    HSC Mathematics Extension 2 or 90 or above in HSC Mathematics Extension 1 or equivalent
MATH1005 or MATH1015 or STAT1021 or ECMT1010 or ENVX1001 or ENVX1002 or BUSS1020 or DATA1001 or DATA1901
Mathematics
MATH1021
Calculus Of One Variable
3    HSC Mathematics Extension 1 or equivalent
MATH1901 or MATH1906 or ENVX1001 or MATH1001 or MATH1921 or MATH1931
MATH1921
Calculus Of One Variable (Advanced)
3    (HSC Mathematics Extension 2) OR (Band E4 in HSC Mathematics Extension 1) or equivalent
MATH1001 or MATH1906 or ENVX1001 or MATH1901 or MATH1021 or MATH1931
MATH1931
Calculus Of One Variable (SSP)
3    (HSC Mathematics Extension 2) OR (Band E4 in HSC Mathematics Extension 1) or equivalent
MATH1001 or MATH1901 or ENVX1001 or MATH1906 or MATH1021 or MATH1921
Enrolment is by invitation only
MATH1023
Multivariable Calculus and Modelling
3    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
MATH1013 or MATH1903 or MATH1907 or MATH1003 or MATH1923 or MATH1933
MATH1923
Multivariable Calculus and Modelling (Adv)
3    (HSC Mathematics Extension 2) OR (Band E4 in HSC Mathematics Extension 1) or equivalent
MATH1003 or MATH1013 or MATH1907 or MATH1903 or MATH1023 or MATH1933
MATH1933
Multivariable Calculus and Modelling (SSP)
3    (HSC Mathematics Extension 2) OR (Band E4 in HSC Mathematics Extension 1) or equivalent
MATH1003 or MATH1903 or MATH1013 or MATH1907 or MATH1023 or MATH1923
Enrolment is by invitation only.
MATH1002
Linear Algebra
3    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)
MATH1012 or MATH1014 or MATH1902
MATH1902
Linear Algebra (Advanced)
3    (HSC Mathematics Extension 2) OR (90 or above in HSC Mathematics Extension 1) or equivalent
MATH1002 or MATH1014

2000-level units of study

Core
DATA2001
Data Science, Big Data and Data Variety
6    DATA1002 OR DATA1902 OR INFO1110 OR INFO1910 OR INFO1903 OR INFO1103 or ENGG1810
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)
DATA2001
DATA2002
Data Analytics: Learning from Data
6    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 [MATH1X05 and (MATH1001 or MATH1002 or MATH1003 or MATH1004 or MATH1021 or MATH1023 or MATH1115 or MATH19XX)]
STAT2012 or STAT2912 or DATA2902
DATA2902
Data Analytics: Learning from Data (Adv)
6    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 above in (DATA1X01 or ENVX1002 or BUSS1020 or ECMT1010 or [MATH1X05 and (MATH1001 or MATH1002 or MATH1003 or MATH1004 or MATH1021 or MATH1023 or MATH1115 or MATH19XX)])
STAT2012 or STAT2912 or DATA2002
Selective
COMP2123
Data Structures and Algorithms
6    P INFO1110 OR INFO1910 OR INFO1113 OR DATA1002 OR DATA1902 OR ENGG1810 OR INFO1103 OR INFO1903
INFO1105 OR INFO1905 OR COMP2823
COMP2823
Data Structures and Algorithms (Adv)
6    P Distinction level results in (INFO1110 OR INFO1910 OR INFO1113 OR DATA1002 OR DATA1902 OR ENGG1810 OR INFO1103 OR INFO1903)
INFO1105 OR INFO1905 OR COMP2123
COSC2002
Computational Modelling
6    HSC Mathematics; DATA1002, or equivalent programming experience, ideally in Python
COSC1003 or COSC1903 or COSC2902
COSC2902
Computational Modelling (Advanced)
6    HSC Mathematics; DATA1002, or equivalent programming experience, ideally in Python
48 credit points of 1000 level units with an average of 65
COSC1003 or COSC1903 or COSC2002
GEGE2001
Genetics and Genomics
6    Mendelian genetics; mechanisms of evolution; molecular and chromosomal bases of inheritance; and gene regulation and expression
GENE2002 or MBLG2972 or GEGE2901 or MBLG2072
GEGE2901
Genetics and Genomics (Advanced)
6    Mendelian genetics, mechanisms of evolution, molecular and chromosomal bases of inheritance, and gene regulation and expression
Annual average mark of at least 70
GENE2002 or MBLG2072 or GEGE2001 or MBLG2972
QBIO2001
Molecular Systems Biology
6    Basic concepts in metabolism; protein synthesis; gene regulation; quantitative and statistical skills
STAT2011
Probability and Estimation Theory
6    (MATH1X21 or MATH1931 or MATH1X01 or MATH1906 or MATH1011) and (DATA1X01 or MATH10X5 or MATH1905 or STAT1021 or ECMT1010 or BUSS1020)
STAT2911
STAT2911
Probability and Statistical Models (Adv)
6    (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)
STAT2011

3000-level units of study

Core interdisciplinary project
DATA3888
Data Science Capstone
6    DATA2001 or DATA2901 or DATA2002 or DATA2902 or STAT2912 or STAT2012
Methodology
COMP3027
Algorithm Design
6    MATH1004 OR MATH1904 OR MATH1064
COMP2123 OR COMP2823 OR INFO1105 OR INFO1905
COMP2007 OR COMP2907 OR COMP3927
COMP3927
Algorithm Design (Adv)
6    MATH1004 OR MATH1904 OR MATH1064
Distinction level results in (COMP2123 OR COMP2823 OR INFO1105 OR INFO1905)
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 ENGG1810 OR DATA1002
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) AND distinction-level results in at least one 2000-level COMP or MATH or SOFT unit
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    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
DATA2001 OR DATA2901 OR ISYS2120 OR INFO2120 OR INFO2820
INFO3504 OR INFO3404
DATA3406
Human-in-the-Loop Data Analytics
6    Basic statistics, database management, and programming
(DATA2001 OR DATA2901) AND (DATA2002 OR DATA2902)
STAT3021
Stochastic Processes
6    Students are expected to have a thorough knowledge of basic probability and integral calculus
STAT2X11
STAT3911 or STAT3011 or STAT3921 or STAT4021
STAT3921
Stochastic Processes (Advanced)
6    Students are expected to have a thorough knowledge of basic probability and integral calculus and to have achieved at credit level or above
STAT2X11
STAT3011 or STAT3911 or STAT3021 or STAT3003 or STAT3903 or STAT3005 or STAT3905 or STAT4021
STAT3022
Applied Linear Models
6    STAT2X11 and (DATA2X02 or STAT2X12)
STAT3912 or STAT3012 or STAT3922 or STAT4022
STAT3922
Applied Linear Models (Advanced)
6    STAT2X11 and [a mark of 65 or greater in (STAT2X12 or DATA2X02)]
STAT3912 or STAT3012 or STAT3022 or STAT4022
STAT3023
Statistical Inference
6    DATA2X02 or STAT2X12
STAT2X11
STAT3913 or STAT3013 or STAT3923
STAT3923
Statistical Inference (Advanced)
6    STAT2X11 and a mark of 65 or greater in (DATA2X02 or STAT2X12)
STAT3913 or STAT3013 or STAT3023
STAT3925
Time Series (Advanced)
6    STAT2X11 and (MATH1X03 or MATH1907 or MATH1X23 or MATH1933)
STAT4025
STAT3926
Statistical Consulting (Advanced)
6    At least 12cp from STAT2X11 or STAT2X12 or DATA2X02 or STAT3XXX
STAT4026
Application
ENVX3001
Environmental GIS
6    P ENVI1003 or AGEN1002 or GEOS1XXX or BIOL1XXX or GEOS2X11
GEOS3X14
ENVX3002
Statistics in the Natural Sciences
6    ENVX2001 or STAT2X12 or BIOL2X22 or DATA2X02 or QBIO2001
AMED3002
Interrogating Biomedical and Health Data
6    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
GEGE3004
Applied Genomics
6    Genetics at 2000 level, Biology at 1000 level, algebra
6cp of (GEGE2X01 or QBIO2XXX or DATA2X01 or GENE2XXX or MBLG2X72 or ENVX2001 or DATA2X02)
ANSC3107
This unit must be taken by all students in the Genetics and Genomics major.
BCMB3004
Beyond The Genome
6    Biochemistry, genetics, cell and/or molecular biology concepts at 2000-level units
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)
BCHM3X92 or BCMB3904
BCMB3904
Beyond The Genome (Advanced)
6    Biochemistry, genetics, cell and/or molecular biology concepts at 2000-level units
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)
BCHM3X92 or BCMB3004
Selective Interdisciplinary Project
SCPU3001
Science Interdisciplinary Project
6    96 credit points
STAT3888
Statistical Machine Learning
6    STAT3012 or STAT3912 or STAT3022 or STAT3922
STAT2X11 and (DATA2X02 or STAT2X12)
STAT3914 or STAT3014