University of Sydney Handbooks - 2017 Archive

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Data Science

 

Graduate Certificate in 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) and the Academic Board policies on Academic Dishonesty and Plagiarism. Up to date versions of all such documents are available from the Policy Register: http://www.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

The attendance pattern for this course is full time or part time according to candidate choice.

3 Master's Type

The master’s degree in these resolutions is an advanced learning master’s course, as defined by the Coursework Rule.

4 Admission to Candidature

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.
(2)
Admission to the Graduate Certificate in Data Science requires:
(a)
A minimum of an AQF level 7 degree in a quantitative discipline, or an AQF level 8 degree in a non-quantitative discipline.
(3)
Admission to the Master of Data Science requires:
(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 Dean 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 or nominee 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 1.
(2)
To qualify for the award of the Graduate Certificate in Data Science:
(a)
Candidates must complete 24 credit points and satisfy the requirements specified in the following clauses.
(b)
Candidates must complete the following Core units of study:
(i)  COMP5310, STAT5002, COMP9007, COMP9120.
(c)
In cases where the Associate Dean 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 1 which complement their prior background and qualifications (subject to assessment by the Academic 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.
(3)
To qualify for the award of the Master in Data Science:
(a)
Candidates must complete 48 credit points and satisfy the requirements specified in the following clauses.
(b)
Candidates must complete the following units of study:
(i)  24 credit points of Core units of study: COMP5310, STAT5003, COMP5318, COMP5048.
(ii)  12 credit points of Project units.
(iii)  a maximum of 12 credit points of non Data Science Elective units of study, as approved by the Academic Director.
(c)
In cases where the Associate Dean 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 1 which complement their prior background and qualifications (subject to assessment by the Academic 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 Academic Director.
(2)
Admission to the Project units of study is subject to availability of supervision and to the approval of the Academic Director.

7 Cross-institutional Study

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

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 Dean, and provided the requirements of the Graduate Certificate have been met.

9 Credit for Previous Study

Credit for previous study may be granted for the Master of Data Science and the Graduate Certificate in Data Science in accordance with the Faculty Coursework Rules for “Credit for previous study” within the “Resolutions of the Faculty (of Engineering and Information Technologies)”, subject to approval by the Academic Director.

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