Master of Data Science (Data Analytics)

University of Southern Queensland

Australia, Toowoomba

University RankQS Ranking

399

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Home/Australia/Toowoomba /University of Southern Queensland/Master of Data Science (Data Analytics)

University of Southern Queensland

Australia , Toowoomba

Key Facts

Program Level

Master by Course Work

Study Type

Full Time

Delivery

Online

Course Code

0101854

Campuses

Toowoomba

Program Language

English

Start & Deadlines

Next Intake Deadlines10-Feb-2026

Apply to this program

Go to the official application for the university

Duration 2 year(s)

Tuition Fee

AUD 31,200 / year(s)

Next Intake 10-Feb-2026

Master of Data Science (Data Analytics)

About

Overview

UniSQ’s Master of Data Science (Data Analytics) provides an opportunity for graduates from all disciplines to gain useful knowledge in Big Data with a specific focus on Data Analytics. Data Science helps organisations to extract new insights from raw data; insights which inform the development of new products, improved services and new businesses in our increasingly data reliant world.
Learn how to find the patterns from the historical data, understand the present, and predict the future using data addressing a wide range of operational contexts.
From big data management, machine learning and data mining, to programming and big data visualisation, you will be prepared for a career in a dynamic and fast-paced industry.
Work independently and collaboratively to apply key ICT and data science technologies and programming skills to interpret major theories and critically investigate and solve contemporary core issues in a global market.
You'll have the opportunity to select between two different pathways of research in your masters degree:
- Research Project track — this pathway equips you with research skills and enables you to develop a research thesis in applied data science through an independent project in your chosen disciplinary application area.
- Research Training track — this pathway allows you to develop your research capability and gain specialised cognitive and technical computational and information system skills to prepare for a professional career in science or your chosen disciplinary application area.

Requirements

Entry Requirements

Entry requirements

3-year bachelor degree from an Australian university, or equivalent, in any area

a minimum of 5 years' professional work experience equivalent to an AQF Level 7 qualification (bachelor).

There are inherent requirements that must be met in order to successfully complete this degree. Inherent requirements are fundamental skills, capabilities and knowledge that students must be able to demonstrate in order to achieve the essential learning outcomes of the degree, while maintaining the academic integrity of the degree. Please read and understand the inherent requirements specific to the Master of Data Science before applying.

If you think you may experience any problems meeting inherent requirements, you can talk to a Student Equity Officer about reasonable adjustments that may be put in place to assist you. Any reasonable adjustments made must not fundamentally change the nature of the inherent requirement.

English language requirements

To meet the English language requirements for this degree, we accept the combined level and duration of study specified below, or the minimum English language proficiency scores from one of the following tests. Your test must be completed within two years of applying to UniSQ.

Tertiary study (Diploma level or higher)	1+ years full-time tertiary study in a country from the Accepted English-speaking countries list.
IELTS (Academic)	Minimum overall score of 6.0 with a minimum 5.5 in each subscore (speaking, listening, writing, reading).
Pearson Test of English	Minimum overall score of 50 with a minimum of 50 in each subscore.
TOEFL iBT	Minimum overall score of 80 with a minimum of 19 in each subscore.

If you do not meet the English language requirements, you can apply to study with our English language partner, the Union Institute of Language (UIL).

English Program Requirements

Recognition of Prior Learning (RPL) allows students to gain credit (advanced standing) towards their course in recognition of skills and knowledge gained through work experience, life experience and/or formal training. Applicants are assessed on a case-by-case basis.

Career

Career outcomes

This degree provides a diverse range of career outcomes with opportunity to advance your profession into any big-data related field. As a graduate, you will become an efficient data scientist, utilising predictive analytics, big data management, big data analysis and modelling, to produce insights that make important, real-life decisions.
Data scientists are highly sought after, and the demand is set to increase as organisations, within technical, engineering, science, business, education and research sectors, require skilled employees to understand and interpret data to benefit business productivity.
Careers may include: Data analyst (within health, marketing etc.), data scientist, data consultant, data engineer, business analyst, supply chain analyst, mining data analyst, fraud data analyst, and data analytics manager.