Computational Data Science major |
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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 |
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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
|
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1000-level units of study |
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Core units |
||
DATA1001 |
6 |
N DATA1901 or MATH1005 or MATH1905 or MATH1015 or MATH1115 or ENVX1001 or ENVX1002 or ECMT1010 or BUSS1020 or STAT1021 |
DATA1901 |
6 |
A An ATAR of 95 or more |
INFO1110 |
6 |
N INFO1910 or INFO1103 or INFO1903 or INFO1105 or INFO1905 or ENGG1810 |
INFO1910 |
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 |
2000-level units of study |
||
Core units |
||
COMP2123 |
6 |
P INFO1110 OR INFO1910 OR INFO1113 OR DATA1002 OR DATA1902 OR ENGG1810 OR INFO1103 OR INFO1903 |
COMP2823 |
6 |
P Distinction level results in (INFO1110 OR INFO1910 OR INFO1113 OR DATA1002 OR DATA1902 OR ENGG1810 OR INFO1103 OR INFO1903) |
DATA2001 |
6 |
P DATA1002 OR DATA1902 OR INFO1110 OR INFO1910 OR INFO1903 OR INFO1103 or ENGG1810 |
DATA2901 |
6 |
P 75% or above from (DATA1002 OR DATA1902 OR INFO1110 OR INFO1910 OR INFO1903 OR INFO1103 or ENGG1810) |
DATA2002 |
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 |
DATA2902 |
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 |
3000-level units of study |
||
Core units |
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DATA3888 |
6 |
P DATA2001 or DATA2901 or DATA2002 or DATA2902 or STAT2912 or STAT2012 |
Selective units |
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COMP3027 |
6 |
A MATH1004 OR MATH1904 OR MATH1064 |
COMP3927 |
6 |
A MATH1004 OR MATH1904 OR MATH1064 |
COMP3308 |
6 |
A Data structures and algorithms as covered in COMP2123 or COMP2823. |
COMP3530 Discrete Optimization |
6 |
|
COMP3608 |
6 |
A Data structures and algorithms as covered in COMP2123 or COMP2823. |
DATA3404 |
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 |
DATA3406 |
6 |
A Basic statistics, database management, and programming |