Data Science major |
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A major in Data Science requires 48 credit points from this table including: |
(i) 12 credit points of 1000-level core units* |
(ii) 12 credit points of 2000-level core units |
(iii) 6 credit points of 2000-level selective units |
(iv) 6 credit points of 3000-level core interdisciplinary project units |
(v) 6 credit points of 3000-level methodology units |
(vi) 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. |
Data Science minor |
A minor in Data Science requires 36 credit points from this table including: |
(i) 12 credit points of 1000-level core units |
(ii) 12 credit points of 2000-level core units |
(iii) 6 credit points of 2000-level selective units |
(iv) 6 credit points of 3000-level methodology units |
Unit of study | Credit points | A: Assumed knowledge P: Prerequisites C: Corequisites N: Prohibition |
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1000-level units of study |
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Core |
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DATA1001 Foundations of Data Science |
6 | A Year 10 mathematics or equivalent N 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 | A Year 10 Mathematics or equivalent; An ATAR of 95 or more N MATH1005 or MATH1905 or ECMT1010 or ENVX1001 or ENVX1002 or BUSS1020 or DATA1001 or MATH1115 or MATH1015 or STAT1021 |
DATA1002 Informatics: Data and Computation |
6 | N INFO1903 or DATA1902 |
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 |
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 |
2000-level units of study |
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Core |
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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 |
Selective |
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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 |
COSC2002 Computational Modelling |
6 | A HSC Mathematics; DATA1002, or equivalent programming experience, ideally in Python N COSC1003 or COSC1903 or COSC2902 |
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 |
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 |
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 |
QBIO2001 Molecular Systems Biology |
6 | A Basic concepts in metabolism; protein synthesis; gene regulation; quantitative and statistical skills |
STAT2011 Probability and Estimation Theory |
6 | P (MATH1X61 or MATH1971 or MATH1X21 or MATH1931 or MATH1X01 or MATH1906 or MATH1011) and (DATA1X01 or MATH1X62 or MATH1972 or MATH10X5 or MATH1905 or STAT1021 or ECMT1010 or BUSS1020) N STAT2911 |
STAT2911 Probability and Statistical Models (Adv) |
6 | P (MATH1X61 or MATH1971 or 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 or MATH1X62 or MATH1972) N STAT2011 |
3000-level units of study |
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Core interdisciplinary project |
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DATA3888 Data Science Capstone |
6 | P DATA2001 or DATA2901 or DATA2002 or DATA2902 or STAT2912 or STAT2012 |
Methodology |
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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) |
STAT3021 Stochastic Processes |
6 | A Students are expected to have a thorough knowledge of basic probability and integral calculus P STAT2X11 N STAT3911 or STAT3011 or STAT3921 or STAT4021 |
STAT3921 Stochastic Processes (Advanced) |
6 | A Students are expected to have a thorough knowledge of basic probability and integral calculus and to have achieved at credit level or above P STAT2X11 N STAT3011 or STAT3911 or STAT3021 or STAT3003 or STAT3903 or STAT3005 or STAT3905 or STAT4021 |
STAT3022 Applied Linear Models |
6 | A Introductory knowledge to linear algebra (MATH1X02 or equivalent) P STAT2X11 and (DATA2X02 or STAT2X12) N STAT3912 or STAT3012 or STAT3922 or STAT4022 |
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 or STAT4022 |
STAT3023 Statistical Inference |
6 | A DATA2X02 or STAT2X12 P STAT2X11 N STAT3913 or STAT3013 or STAT3923 |
STAT3923 Statistical Inference (Advanced) |
6 | P STAT2X11 and a mark of 65 or greater in (DATA2X02 or STAT2X12) N STAT3913 or STAT3013 or STAT3023 |
STAT3925 Time Series (Advanced) |
6 | P STAT2X11 and (MATH1062 or MATH1962 or MATH1972 or MATH1X03 or MATH1907 or MATH1X23 or MATH1933) N STAT4025 |
STAT3926 Statistical Consulting (Advanced) |
6 | P A mark of 65 or greater in DATA2X02 N STAT4026 |
Application |
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ENVX3001 Environmental GIS |
6 | P ENVI1003 or AGEN1002 or GEOS1XXX or BIOL1XXX or GEOS2X11 N GEOS3X14 |
ENVX3002 Statistics in the Natural Sciences |
6 | P ENVX2001 or STAT2X12 or BIOL2X22 or DATA2X02 or QBIO2001 |
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 P DATA1X01 or 48 credit points of any 1000 or 2000-level units in (ANAT or AVBS or BCMB or BIOL or BIOS or CHEM or COMP or COSC or DATA or ENVX or EXSS or FOOD or FMHU or GEGE or HPSC or HSBH or IMMU or MATH or MEDS or MICR or MIMI or PCOL or PHSI or PHYS or PSYC or QBIO or STAT) |
GEGE3004 Applied Genomics |
6 | A Genetics at 2000 level, Biology at 1000 level, algebra P 6 credit points 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. |
BCMB3004 Beyond the Genome |
6 | A Biochemistry, genetics, cell and/or molecular biology concepts at 2000-level units 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 BCHM3X92 or BCMB3904 |
BCMB3904 Beyond the Genome (Advanced) |
6 | A Biochemistry, genetics, cell and/or molecular biology concepts at 2000-level units 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 |
Selective Interdisciplinary Project |
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SCPU3001 Science Interdisciplinary Project |
6 | P 96 credit points N HSBH3026 |
STAT3888 Statistical Machine Learning |
6 | A STAT3012 or STAT3912 or STAT3022 or STAT3922 P STAT2X11 and (DATA2X02 or STAT2X12) N STAT3914 or STAT3014 |