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Overview

The Master of Data Science degree explores more ways to organise, identify, analyse and ultimately use data to inform strategies, redefine ambiguous questions and find answers that make a genuine impact. Students will develop advanced technical and mathematical skills to unpick complexities and make sense of the numbers. Study for … For more content click the Read More button below.

Learning Outcomes

1.
Prepare, analyse, interpret and present data to provide useful insights for business decision making.
  • Leaders
  • Scholars
2.
Demonstrate cultural, professional and ethical competence to become a responsible Data Scientist and a global citizen.
  • Global citizens
  • Professionals
3.
Research and apply enquiry-based learning, including, analysis and critical thinking, reflection, and problem solving, to become a lifelong learner and an innovative and self directed professional.
  • Scholars
  • Leaders
  • Professionals
4.
Collaborate and lead interdisciplinary teams
  • Leaders
5.
Communicate effectively in written and oral formats to engage specialist and non-specialist audiences.
  • Leaders
6.
Synthesise, evaluate and integrate a complex body of knowledge underpinning data science practice including statistics, computer science, applied mathematics and business strategies.
  • Scholars

Enrolment Disclaimer

Please note that this Handbook is a comprehensive catalogue of our offerings and includes courses that can be taken to satisfy program requirements irrespective as to their availability for a particular year. Availability of courses is best checked using filters on this site or on the class timetable site.

You are responsible for ensuring that you enrol in courses according to your program requirements and by following the advice of your Program Authority. myUNSW enrolment checks that you have met enrolment requirements such as pre-requisites for individual courses but not that you are enrolling in courses that will count towards your program requirements.

Admission Requirements

Entry Requirements

Minimum Entry Requirements

Limitations on Recognition of Prior Learning

Program Requirements

Progression Requirements

A credit average is generally required to articulate to the next level in the sequence.

For more information on university policy on progression requirements please visit Academic Progression

Associated Programs

Similar Program

Master of Data Science and Decisions - MDataSci8959 - Data Science and Decisions

Postgraduate Pathway

Doctor of Philosophy - PhD1880 - Mathematics and Statistics
Master of Philosophy - MPhil2645 - Engineering
Master of Science (Research) - MSc(Res)2920 - Mathematics and Statistics (MRes)

Nested Postgraduate Program

Graduate Diploma in Data Science - GDDS5646 - Data Science
Graduate Certificate in Data Science - GCDS7446 - Data Science

Professional Outcomes

Career Opportunities

Database and Systems Administrators, ICT Security Specialists, Statisticians, Data Scientists.

Recognition of Achievement

Award with Excellence
For more information, please visit the link above.
The Award with Excellence is awarded in coursework masters programs, including Masters (Extension) but with the exception of Masters (Extended) such as JD and MD, when a Weighted Average Mean (WAM) of at least 80% has been achieved and at least 50% of the requirements of the award are completed at UNSW. All eligible programs will award 'with Excellence' except in special circumstances where approval of Academic Board has been given for a program to opt out.

Program Fees

At UNSW fees are generally charged at course level and therefore dependent upon individual enrolment and other factors such as student's residency status. For generic information on fees and additional expenses of UNSW programs, click on one of the following:

Pre-2019 Handbook Editions

Access past handbook editions (2018 and prior)