Data Science
Master of Data Science
These resolutions must be read in conjunction with applicable University By-laws, Rules and policies including (but not limited to) the University of Sydney (Coursework) Rule 2014 (the 'Coursework Rule'), the Coursework Policy 2014, the Resolutions of the Faculty, the University of Sydney (Student Appeals against Academic Decisions) Rule 2006 (as amended), the Academic Honesty in Coursework Policy 2015 and the Academic Honesty Procedures 2016. Up to date versions of all such documents are available from the Policy Register: http://sydney.edu.au/policies.
Course resolutions
1 Course codes
|
Code |
Course title |
|---|---|
|
GCDATASC-01 |
Graduate Certificate in Data Science |
|
MADATASC-01 |
Master of Data Science |
2 Attendance Pattern
3 Master's Type
0.
The master’s degree in these resolutions is an advanced learning master’s course, as defined by the Coursework Policy.
4 Admission to Candidature
0.
Definition: A Quantitative discipline includes Data Science, Computer Science, Mathematics, Statistics, Engineering, Physics, Economics, Finance or other disciplines that are deemed Quantitative by the Academic Director. As a guideline, the curriculum of a Quantitative discipline should include a minimum of 12 credit points of mathematics or statistics at the tertiary level.
(1)
Available places will be offered to qualified applicants based on merit, according to the following admissions criteria.
(a)
A minimum of an AQF level 7 degree in a quantitative discipline, or an AQF level 8 degree in a non-quantitative discipline.
(a)
A minimum of an AQF level 8 equivalent qualification in a Quantitative discipline with at least a credit average;
(b)
Other students with a high level of relevant achievement may be admitted provided the relevant delegated authority is satisfied they have achieved learning outcomes equivalent to a level 8 award in a Quantitative discipline with at least a credit average.
(4)
In exceptional circumstances the Dean may admit applicants without these qualifications who, in the opinion of the faculty, have qualifications and evidence of experience and achievement sufficient to successfully undertake the award.
5 Requirements for Award
(1)
The units of study that may be taken for the course/s are set out in Table A for the Master of Data Science.
(c)
In cases where the relevant delegated authority waives the requirement for a student to complete a compulsory unit of study (under 46(1) of the Coursework Policy 2014), the student will be required to select Core or Data Science Elective units from Table A which complement their prior background and qualifications (subject to assessment by the Program Director) as may be necessary to satisfy the requirements of the degree.
(i) Where a waiver is granted for a COMP core unit of study, another COMP unit must be taken, and where the waiver is granted for STAT5002, another STAT unit of study must be taken.
(a)
Candidates must complete 48 credit points and satisfy the requirements specified in the following clauses.
(iv) a maximum of 12 credit points of non Data Science Elective units of study, as approved by the relevant delegated authority.
(c)
In cases where the relevant delegated authority waives the requirement for a student to complete a compulsory unit of study (under 46(1) of the Coursework Policy 2014) the student will be required to select Core or Data Science Elective units from Table A which complement their prior background and qualifications (subject to assessment by the Program Director) as may be necessary to satisfy the requirements of the degree.
(i) Where a waiver is granted for a COMP core unit of study another COMP unit must be taken and where the waiver is granted for STAT5003 another STAT unit of study must be taken.
6 Progression Rules
(1)
A candidate for the Master of Data Science must complete 24 credit points from Core and Elective units of study before taking Data Science Capstone Project Units. Candidates who do not achieve a credit average may have their eligibility for the Capstone Project subject to review by the Program Director.
(2)
Admission to the Project units of study is subject to availability of supervision and to the approval of the Program Director.
7 Cross-institutional Study
0.
Cross-institutional study is not available in these courses except where the University of Sydney has a formal cooperation agreement with another university.
8 Course Transfer
0.
A candidate for the Master of Data Science degree may elect to discontinue study and graduate with the Graduate Certificate in Data Science, with the approval of the relevant delegated authority, and provided the requirements of the Graduate Certificate have been met.