Data Science
Errata
| Item | Errata | Date |
|---|---|---|
| 1. |
The prerequisites have been removed for the following units: MATH1021 Calculus Of One Variable |
12/12/2018 |
| 2. |
The prerequisites have been removed and the assumed kowledge has changed for the following units: MATH1921 Calculus Of One Variable (Advanced): Prerequisites have been removed. Assumed knowledge now reads: (HSC Mathematics Extension 2) OR (Band E4 in HSC Mathematics Extension 1) or equivalent. MATH1931 Calculus Of One Variable (SSP): Prerequisites have been removed. Assumed knowledge now reads: (HSC Mathematics Extension 2) OR (Band E4 in HSC Mathematics Extension 1) or equivalent. MATH1923 Multivariable Calculus and Modelling (Adv): Prerequisites have been removed. Assumed knowledge now reads: (HSC Mathematics Extension 2) OR (Band E4 in HSC Mathematics Extension 1) or equivalent MATH1933 Multivariable Calculus and Modelling (SSP):Prerequisites have been removed. Assumed knowledge now reads: (HSC Mathematics Extension 2) OR (Band E4 in HSC Mathematics Extension 1) or equivalent. |
12/12/2018 |
| Unit of study | Credit points | A: Assumed knowledge P: Prerequisites C: Corequisites N: Prohibition | Session |
|---|---|---|---|
DATA SCIENCE |
|||
| Advanced coursework and projects will be available in 2020 for students who complete this major. | |||
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 or STAT1022 |
Semester 1 Semester 2 |
| DATA1901 Foundations of Data Science (Adv) |
6 | A An ATAR of 95 or more N MATH1905 or ECMT1010 or ENVX2001 or BUSS1020 or DATA1001 or MATH1115 |
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 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 STAT1022 or ECMT1010 or ENVX1001 or ENVX1002 or BUSS1020 or DATA1001 or DATA1901 |
Semester 1 Semester 2 Summer Main |
Computation |
|||
| MATH1115 Interrogating Data |
3 | P MATH1005 or MATH1015 N STAT1021 or STAT1022 or ENVX1001 or ENVX1002 or BUSS1020 or ECMT1010 or DATA1001 or DATA1901 |
Semester 1 Semester 2 Summer Main |
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 STAT1022 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. P NSW HSC 2 unit Mathematics or equivalent or a credit or above in MATH1111 N MATH1011 or MATH1901 or MATH1906 or ENVX1001 or MATH1001 or MATH1921 or MATH1931 |
Semester 1 Semester 2 Summer Main |
| MATH1921 Calculus Of One Variable (Advanced) |
3 | A HSC Mathematics Extension 2 or equivalent. P NSW HSC 2 unit Mathematics or equivalent or a credit or above in MATH1111 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 Band 4 in HSC Mathematics Extension 2 or equivalent. P NSW HSC 2 unit Mathematics or equivalent or a credit or above in MATH1111 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 MATH1X21, HSC Mathematics Extension 1 or equivalent. P NSW HSC 2 unit Mathematics or equivalent or a credit or above in MATH1111 N MATH1013 or MATH1903 or MATH1907 or MATH1003 or MATH1923 or MATH1933 |
Semester 1 Semester 2 Summer Main |
| MATH1923 Multivariable Calculus and Modelling (Adv) |
3 | A MATH1X21, HSC Mathematics Extension 2 or equivalent. P NSW HSC 2 unit Mathematics or equivalent or a credit or above in MATH1111 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 MATH1X21, Band 4 in HSC Mathematics Extension 2 or equivalent. P NSW HSC 2 unit Mathematics or equivalent or a credit or above in MATH1111 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 |
Semester 1 Summer Main |
| MATH1902 Linear Algebra (Advanced) |
3 | A (HSC Mathematics Extension 2) OR (90 or above in HSC Mathematics Extension 1) or equivalent N MATH1002 or MATH1012 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 P [DATA1001 or ENVX1001 or ENVX1002] or [MATH10X5 and MATH1115] or [MATH10X5 and STAT2011] 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 (MATH1905 and MATH1XXX [except MATH1XX5]) or (QBUS1020 or ECMT1020 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 Note: Department permission required for enrolment |
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 |
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 |
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 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 |
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 | 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 Note: Department permission required for enrolment |
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 |
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 BIOM2001 or STAT2X12 or BIOL2X22 or DATA2002 or QBIO2001 Interdisciplinary Unit |
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 2019 |
6 | P QBUS2810 or DATA2002 or ECMT2110 N ECMT3180 |
Semester 1 |
Selective Interdisciplinary Project |
|||
| SCPU3001 Science Interdisciplinary Project |
6 | P Completion of 2000-level units required for at least one Science major. |
Intensive December Intensive February Intensive January Intensive July Semester 1 Semester 2 |