University of Southern Queensland
Master of Data Science (Data Analytics)
- Delivery: Face to Face
- Study Level: Postgraduate
- Duration: 24 months
- Course Type: Master's
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.

Course 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.
CSP Subsidised Fees Available
This program has a limited quota of Commonwealth Supported Places (CSP). The indicative CSP price is calculated based on first year fees for EFT. The actual fee may vary if there are choices in electives or majors.
Key facts
What you will study
The program consists of 16 units comprising of:
- Eight units of core ICT courses
- Four units of specialisation
- Four units of elective courses
Core Units (eight units)
- Big Data Management
- Machine Learning
- Data Mining
- Foundations of Programming
- IS/ICT Project Management
- Multivariate Analysis for High-Dimensional Data
- Advanced ICT Professional Project
- Statistics for Quantitative Researchers
Specialisation (four units)
Select one of the following specialisation:
- Artificial Intelligence and Machine Learning
- Data Analytics
Electives (four units)
Select one of the following three (3) options:
- Research Dissertation
- Applied Research Skills
- Any four (4) postgraduate courses
Entry requirements
Applicants must have one of the following:
- Three-year bachelor degree from an Australian university, or equivalent, in any area .
- A minimum of five 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 the English for Academic Purposes EAP2 pathway program through the Union Institute of Language (UIL).
Recognition of Prior Learning
If you have previously studied in your home country, you may be eligible for recognition of prior learning to reduce the number of courses that you need to study to finish your program.
Outcomes
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.
Learning outcomes
Upon completion of this program, graduates will be able to:
- Autonomously apply key ICT and data science professional knowledge, technologies and programming skills to critically investigate and analyse contemporary core issues in a global market and to develop big data analysis and evidence-based decision-making skills.
- Select, adapt and apply specialised quantitative and technical skills to work independently and collaboratively to process and interpret major theories and concepts associated with big data to solve and interpret complex and real-life problems.
- Work under broad direction within a team environment, manage conflict and take a leadership role for a task within the project.
- Apply and communicate ethical, legal and professional standards related to big data privacy and building of a security culture and assess and evaluate risks in order to comply with customer organisational requirements.
- Investigate, critically analyse, evaluate and communicate research findings and problem solutions associated with applied data theories and methodologies to specialist and non-specialist audiences.
Fees and CSP
Indicative annual fee in 2025: $28,960 (domestic full-fee paying place)
Indicative annual fee in 2025: $9,312 (Commonwealth Supported Place)
A student’s annual fee may vary in accordance with:
- The number of units studied.
- The choice of major or specialisation.
- Choice of courses.
- Credit from previous study or work experience.
- Eligibility for government-funded loans.
Student fees shown are subject to change. Contact the university directly to confirm.
Commonwealth Supported Places
The Australian Government allocates a certain number of CSPs to the universities each year, which are then distributed to students based on merit.
If you're a Commonwealth Supported Student (CSS), you'll only need to pay a portion of your tuition fees. This is known as the student contribution amount – the balance once the government subsidy is applied. This means your costs are much lower.
Limited CSP spaces are offered to students enrolled in selected postgraduate courses.
Your student contribution amount is:
- Calculated per courses you're enrolled in.
- Dependent on the study areas they relate to.
- Reviewed and adjusted each year.
HECS-HELP loans are available to CSP students to pay the student contribution amount.
FEE-HELP loans are available to assist eligible full-fee paying domestic students with the cost of a university course.