Course Overview

About This Course

Be at the cutting edge of the booming field of data science and develop specialised skills that can be applied across industries. Drive real change and impact key decisions by learning how to make sense of the volume, variety, and velocity of data we collect as a society.

Where You Can Study

Available Locations

BRISBANE

2 George St, BRISBANE, QLD 4000

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Eligibility

Entry Requirements

General Requirements

No specific entry requirements for the Bachelor of Mathematics / Master of Data Science double degree were listed on this page.
General postgraduate CSP eligibility requires applicants to be a domestic student and satisfy one of the following residency requirements:
- Australian citizen who will undertake at least one unit of study in Australia that contributes to their course of study
- New Zealand citizen living in Australia for the teaching period, unless the course requires living elsewhere
- Holder of an Australian permanent visa (including humanitarian visa holders), living in Australia for the teaching period, unless the course requires living elsewhere

Career & Study Pathways

Where this takes you

Career Opportunities

Graduates develop specialised data science skills that can be applied across industries, enabling them to drive real change and impact key decisions by making sense of the volume, variety, and velocity of data collected as a society. Data science skills are in high demand as data becomes the main driver for business decision-making across many industries.

Quality & Recognition

Accreditation & Migration

Academic Regulator

TEQSA

Professional Body

Australian Computer Society (ACS)

Accreditation Status

Accredited

Skills Assessor

ACS

Common Questions

Frequently Asked Questions

What is the duration of the Bachelor of Mathematics / Master of Data Science?

The Master of Data Science component can be completed in 1-2 years full-time or 2-4 years part-time. As a vertical double degree, it seamlessly integrates the undergraduate Bachelor of Mathematics with the Master of Data Science.

Are there any fee savings available for this course?

QUT has introduced Commonwealth Supported Places (CSPs) for 10 in-demand IT, data science and business process management courses, allowing you to save more than 60% on tuition fees.

Who teaches the data science courses at QUT?

When you study data science and analytics at QUT, you learn from leading experts who are active researchers in the QUT Centre for Data Science, led by the internationally-renowned statistician, Distinguished Professor Kerrie Mengersen.

What is the QUT Centre for Data Science?

The QUT Centre for Data Science brings together the university's strengths and track record in data analysis, computation and eResearch, as well as cross-disciplinary projects and connections to centres of excellence, cooperative research centres, and national and international networks.

What other pathways are available if I want to study data science at a lower level before committing to a master degree?

QUT offers a Graduate Certificate in Data Science, which provides an opportunity to further your knowledge in additional fields such as statistical data analysis, programming fundamentals, data manipulation or business process modelling, and can be completed in 1-2 years part-time.

Application

How to Apply

Three simple steps to get enrolled

Step 01

Enquire

Click "Enquire Now" and tell us a little about yourself. It's free and takes 2 minutes.

Step 02

Submit Documents

Our team will guide you on exactly which documents to prepare and submit.

Step 03

Get Enrolled

Receive your offer letter and confirm your enrolment. Welcome to the course!

Course Snapshot

Salary, careers & skills

Typical Salary

Entry-level (0-2 years)AUD $70,000 to $90,000 per year

Early Career (2-5 years)AUD $90,000 to $115,000 per year

Mid-Level (5-10 years)AUD $115,000 to $160,000 per year

Career Paths

Data ScientistData AnalystBusiness Intelligence (BI) AnalystMachine Learning EngineerData Engineer

Key Skills

Programming in Python and R for data analysis, modelling, and automationSQL and database querying for data extraction and managementMachine learning algorithm development and model trainingStatistical analysis and hypothesis testingData visualisation using tools such as Tableau and Power BI

Full Course Overview

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