Course

Master of Data Science

Approved Abbreviation: MDataSc


Western Sydney University Course Code: 3735.1

AQF Level: 9

CRICOS Code: 089442E


Course Status: CONTINUING
This version of the course is available only to continuing or completing 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 2016 or later.

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

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

Assumed Knowledge:

For a student to successfully complete this course they will need to have an understanding of Mathematics equivalent to 2-unit HSC, and experience with the use of computer software such as Excel or Word. Previous experience of statistics or computer programming will be an advantage but is not essential.

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.

Recommended Sequence

Start-year Intake

Year 1

Autumn session

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

Spring session

301044Data Science
301115Advanced Statistical Methods
301117Predictive Analytics

And one elective

Year 2

Autumn session

300597Master Project 1

From 2021, students are advised to select 301384 Postgraduate Project A which has replaced 300597. The units are equivalent.

301384Postgraduate Project A
301116Social Media Intelligence
301118Genomic Data Science

From 2021, students are advised to select 301365 Probabilistic Graphical Models which has replaced 301118.

301365Probabilistic Graphical Models

And one elective

Spring session

300598Master Project 2

From 2021, students are advised to select 301385 Postgraduate Project B which has replaced 300598. The units are equivalent.

301385Postgraduate Project B
301119Advanced Machine Learning

And two electives

All elective units must be at Postgraduate Level 7

Elective units may be used towards obtaining the approved specialisation ST3063 Space Science

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

300597Master Project 1
301115Advanced Statistical Methods
301117Predictive Analytics
301119Advanced Machine Learning

Autumn session

300598Master Project 2
301118Genomic Data Science

From 2021, students are advised to select 301365 Probabilistic Graphical Models which has replaced 301118.

301365Probabilistic Graphical Models

And two electives

All elective units must be at Postgraduate Level 7

Elective units may be used towards obtaining the approved specialisation ST3063 Space Science

ST3063Space Science
ST3075Artificial Intelligence


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