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Master of Data Science

Approved Abbreviation: MDataSc


Western Sydney University Course Code: 3735.2

AQF Level: 9

CRICOS Code: 089442E


Course Status: CURRENT
This version of the course is available to new and continuing students.


Students should follow the course structure for the course version relevant to the year they commenced. This version applies to students whose commencement year in this course was 2021 or later.

Units may be revised or replaced to ensure students are provided with up to date curriculum throughout their studies, and this may result in a new course version. Refer to the Check My Course Progress page in MySR for the most up to date information for your course.

Commencement year 2016 - 3735.1 - Master of Data Science

Increasingly in the digital age data plays an important role in most, if not all, occupations. Extracting information from data has become a science in itself, blending skill sets from mathematics, statistics and computing. With a strong applications focus, this course covers the nature of data including Big and Unstructured Data, how to embark on data driven investigations and visual and computational analytics. The course graduates will have the knowledge and skills required to operate effectively in a data driven world.

Study Mode
Two years full-time or four years part-time.

Course Advice

NameEmail
Course AdviceCDMS@westernsydney.edu.au
Prospective students should use the links at the top of the page for general enquiries about this course.

Location

CampusAttendanceModeCourse Advice
Parramatta Campus - Victoria RoadFull TimeInternal See above
Parramatta Campus - Victoria RoadPart TimeInternal See above

Admission

To enter the Master of Data Science program applicants must have successfully completed an undergraduate degree, or higher, in any discipline.

Additional Information

Previous experience of statistics or computer programming will be an advantage but is not essential.

Applicants with the following may be eligible to receive up to 80 credit points in advanced standing:

  • an undergraduate degree in data science and 2 years full-time equivalent managerial/professional work experience in roles relating to data science, machine learning, statistician, data analyst or associated roles;
  • OR
  • a graduate certificate, or higher, in data science.

Applicants seeking admission on the basis of work experience must support their application with a Statement of Service for all work experience listed on the application.

Statement of Service

Applications from Australian and New Zealand citizens and holders of permanent resident visas must be made via the Universities Admissions Centre (UAC). Use the links below to apply via UAC or Western Sydney University.  Applications made directly to Western Sydney do not have an application fee.

Applicants who have undertaken studies overseas may have to provide proof of proficiency in English. Local and International applicants who are applying through the Universities Admissions Centre (UAC) will find details of minimum English proficiency requirements and acceptable proof on the UAC website. Local applicants applying directly to the University should also use the information provided on the UAC website.

http://www.uac.edu.au/

https://westernsydney.uac.edu.au/ws/

International applicants must apply directly to Western Sydney University via the International Office.

International students applying to The University through the International Office can find details of minimum English proficiency requirements and acceptable proof on their website.

International Office

Overseas qualifications must be deemed by the Australian Education International - National Office of Overseas Skills Recognition (AEI-NOOSR) to be equivalent to Australian qualifications in order to be considered by UAC and Western Sydney University.

Course Structure

Qualification for this award requires the successful completion of 160 credit points which include the units listed in the recommended sequence below.

Note: Students may be able to receive a maximum of 80 credit points of advanced standing depending on previous studies and after consultation with the Director of Academic Program.

Recommended Sequence

Start-year Intake

Year 1

Autumn session

301113Programming for Data Science
301114The Nature of Data
301046Big Data
301112Visualisation

Spring session

301044Data Science
301115Advanced Statistical Methods
301117Predictive Analytics

And one elective

Year 2

Autumn session

301116Social Media Intelligence
301384Postgraduate Project A
301365Probabilistic Graphical Models

And one elective

Spring session

301119Advanced Machine Learning
301385Postgraduate Project B

And two electives

Elective spaces

Elective units must be at Postgraduate Level 7.

Elective units may be used towards obtaining the approved specialisations

ST3063Space Science
ST3075Artificial Intelligence

Mid-year Intake

Year 1

Spring session

301044Data Science
301113Programming for Data Science
301114The Nature of Data

And one elective

Autumn session

301046Big Data
301112Visualisation
301116Social Media Intelligence

And one elective

Year 2

Spring session

301115Advanced Statistical Methods
301119Advanced Machine Learning
301117Predictive Analytics
301384Postgraduate Project A

Autumn session

301365Probabilistic Graphical Models
301385Postgraduate Project B

And two electives

Elective spaces

Elective units must be at Postgraduate Level 7.

Elective units may be used towards obtaining the approved specialisations

ST3063Space Science
ST3075Artificial Intelligence


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