Note: This course version is currently under review and is subject to change.

ProgramsSCSCS(PG)DataSciMaster of Data Science (2022 and earlier) (2017)


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Year 1 - Semester 1

SITS Diet Block/TypeCPUnit of Study/Unit Block
Core
6COMP5310: Principles of Data Science
Core
6COMP5318: Machine Learning and Data Mining
List
12Select from
Data Science Elective
Non Data Science Electives

Year 1 - Semester 2

SITS Diet Block/TypeCPUnit of Study/Unit Block
Core
6COMP5048: Visual Analytics
Core
6STAT5003: Computational Statistical Methods
12Select from
Data Science Project

Note:   The tables above assume completion in 1 year by taking a full-time load of 24 credit points per semester. When studied part-time, the duration of the Master of Data Science extends correspondingly.

The prerequisites for STAT5003 are waived for Master of Data Science students. Please apply through Special Permission for this unit.

You can also refer to additional enrolment guides for:

Semester 1 entry - http://sydney.edu.au/engineering/it/~roehm/docs/MDS-EnrolmentGuide-2017sem1.pdf

Semester 2 entry - http://sydney.edu.au/engineering/it/~roehm/docs/MDS-EnrolmentGuide-2017sem2.pdf

No streams/majors defined for this course version.

Block 1 - Data Science Core

Unit Code Unit Name CP Sessions Offered
COMP5048 Visual Analytics 6 Semester 1
Semester 2
COMP5310 Principles of Data Science 6 Semester 1
Semester 2
COMP5318 Machine Learning and Data Mining 6 Semester 1
Semester 2
STAT5003 Computational Statistical Methods 6 Semester 1
Semester 2

Note: Without waiver, candidates must complete: COMP5310, STAT5003, COMP5318, COMP5048.

Please note that students with a Graduate Certificate in Data Science still need to complete 48 cpts in a subsequent Master of Data Science - there is no credit transfer. In this case, we give however a waiver for COMP5310, and affected students enrol in a third Elective Unit instead. For a visualisation, see the following diagram: http://sydney.edu.au/engineering/it/~roehm/docs/GCDS-to-MDS-Pathway.png

Block 2 - Data Science Project (Min CP: 12,Max CP: 12)

Unit Code Unit Name CP Sessions Offered
COMP5703 Information Technology Capstone Project 12 Semester 1
Semester 2
COMP5707 Information Technology Capstone A 6 Semester 1
Semester 2
COMP5708 Information Technology Capstone B 6 Semester 1
Semester 2

Note: 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.

Block 3 - Data Science Elective (Max CP: 18)

Unit Code Unit Name CP Sessions Offered
COMP5046 Natural Language Processing 6 Semester 1
COMP5338 Advanced Data Models 6 Semester 2
COMP5349 Cloud Computing 6 Semester 1
COMP5425 Multimedia Retrieval 6 Semester 1
INFO5060 Data Analytics and Business Intelligence 6 Int July
INFO5301 Information Security Management 6 Semester 1
Semester 2
QBUS6810 Statistical Learning and Data Mining 6 Semester 1
Semester 2
QBUS6840 Predictive Analytics 6 Semester 1

Note: The prerequisites for QBUS6810 and QBUS6840 are waived for Master of Data Science students. Please apply through Special Permission for these units.

Block 4 - Non Data Science Electives (Max CP: 12)

Unit Code Unit Name CP Sessions Offered
EDPC5012 Evaluating Learning Technology Innovation 6 Semester 1
EDPC5025 Learning Technology Research Frontiers 6 Semester 2
ITLS6107 Applied GIS and Spatial Data Analytics 6 Semester 2
Summer Main
PHYS5033 Environmental Footprints and IO Analysis 6 Semester 1
Semester 2

Note: Non Data Science electives may be chosen from any discipline, as appropriate and approved by Academic Director.

Course: Master of Data Science (2022 and earlier) (2017)
CP Required: 48
Min FT Duration: 1.00 Years
Min PT Duration: 2.00 Years
Faculty/School: Faculty of Engineering
Years Offered: 2022, 2021, 2020, 2019, 2018, 2017, 2016
Requirements: To qualify for the award of the Master in Data Science, candidates must complete 48 credit points, including:

i. 24 credit points of Core units of study: COMP5310, COMP5318, COMP5048, STAT5003.

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.

Please note that students with a Graduate Certificate in Data Science still need to complete 48 cpts in a subsequent Master of Data Science - there is no credit transfer. The Associate Dean will give a waiver for COMP5310 to holders of a Graduate Certificate of Data Science, and affected students enrol in a third Elective Unit instead. See also: http://sydney.edu.au/engineering/it/~roehm/docs/GCDS-to-MDS-Pathway.png

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 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.

- 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.

For further details of the course rules, see the Faculty Handbook at http://sydney.edu.au/handbooks
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