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Every industry needs expertise in data science

Be at the front of this fast-moving field of technology

Our rankings

Drive business decision-making

  • 61st in the world

    Ranked 61st globally for engineering and technology by the 2020 QS University Rankings by Subject

  • 1st for employability

    Our graduates are ranked 1st in Australia and 4th globally for employability by the 2020 QS Graduate Employability Rankings

Overview

The Master of Data Science is a professional degree for people who are passionate about drawing meaningful knowledge from data to drive business decision-making or research output. It will develop your analytical and technical skills to use data science to guide strategic decisions in your area of expertise. It also offers the flexibility to tailor learning to your professional and personal interests.

Data is a vital asset to any organisation. It holds valuable insights into areas such as customer behaviour, market intelligence and operational performance. Data scientists build intelligent systems to manage, interpret, understand and derive key knowledge from big data sets. If you have a strong mathematical or quantitative backgrounds, this degree will develop your analytical and technical skills in using data science to guide strategic decisions in your area of expertise.

Leveraging the University of Sydney's research strengths, you will explore the latest in data mining, machine learning and data visualisation, while developing the skills to communicate data insights to key stakeholders effectively.

If you have qualifications in areas such as health and education, a Graduate Certificate in Data Science can provide you with the data science capability to complement your existing skills and provide a pathway to the master's program.

Subject areas

This course has no specialisation or major.

Shared pool

Entry, fees, funding & how to apply

Depends on your qualification, citizenship status
The details on this page based on your selections are a guide only, and are subject to change.

Your entry requirements

English language proficiency

Find out if you need to prove English language proficiency (depends on your country of origin and educational background).

For academic requirements check the ‘Admission requirements’ section on this page.

Your fee

How to apply

You can apply online via the application portal. When you are ready to apply, select the ‘Apply’ button on this course page. Visit the How to apply page for other important information. 

Standard closing dates:

Semester 1 - 11 February of the commencing year
Semester 2 - 15 July of the commencing year

We strongly encourage applicants to apply as early as possible, offers are made on a rolling basis and places are limited. Separate scholarship deadlines apply - check the scholarships website for details.

Starting date

Semester 1 (March) and Semester 2 (August)

You can apply online via the application portal. When you are ready to apply, select the ‘Apply’ button on this course page. Visit the How to apply page for other important information. 

Standard closing dates:

Semester 1 - 31 January of the commencing year
Semester 2 - 30 June of the commencing year

We strongly encourage international applicants to apply as early as possible to allow time for visa and travel arrangements. Separate scholarship deadlines may apply - check the scholarships website for details.

Starting date

Semester 1 (March) and Semester 2 (August)

Admission criteria

To be eligible for admission, an applicant is required to have:

  • a four year Australian bachelor's degree with honours in a quantitative discipline* with a minimum credit average (65 percent), or
  • an equivalent qualification with a research component or an Australian master's degree in a quantitative discipline* with a minimum credit average (65 percent), or equivalent qualification, or
  • the University of Sydney Graduate Certificate in Data Science with a minimum credit average (65 percent), or equivalent or higher qualification

There is no credit transfer possible between the Graduate Certificate in Data Science and the Master of Data Science. Students with a Graduate Certificate in Data Science still need to complete 48 credit points in a subsequent Master of Data Science. They will receive a waiver for COMP5310, and can hence enrol in a third Elective Unit instead.

*A quantitative discipline includes data science, computer science, mathematics, statistics, engineering, physics, economics, finance or other disciplines that are deemed equivalent. As a guideline, the curriculum of a quantitative discipline should include some study of mathematics including statistics at the tertiary level.

Some background in computing (specifically in programming and in data management as taught in the Graduate Certificate in Data Science) is assumed. Applicants who hold a three year bachelor's degree without honours in a quantitative discipline can apply to the Master of Data Science based on employment experience if they can demonstrate a minimum of two years relevant industry experience in IT or Data Science/Data Analytics. This must be supported by a CV and proof of work experience (in the form of an official letter from the employer including details of your position, dates of employment and job description). If you have completed an honours degree in a non-quantitative discipline, you may be eligible for the Graduate Certificate in Data Science. 

Career Pathways

The Master of Data Science will provide the knowledge, skills and experience to equip the graduate to operate independently as a data scientist within any application domain. The training it provides also supports several career paths, by: honing data skills at the frontier of machine intelligence research to become a data scientist for hire; up-skilling to build intelligent data-driven systems in an existing area of expertise (e.g., mining analyst); improving scientific research through training in data management, analysis, and modelling.
Future study options

The University of Sydney is a research intensive institution with a strong track record of technology transfer and commercialisation. Research activities in the School of Information Technologies focus on algorithmics and applications, enterprise computing, human-centred computing, and IT applications in health care. If you would like to be part of Sydney's IT research community, you may consider applying for admission to a higher degree by research. Students completing a research degree undertake supervised research and submit a written thesis at the completion of their studies in the degree of Master of Philosophy or Doctor of Philosophy.

Domestic students

International students

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