Master of Data Science (Artificial Intelligence and Machine Learning)

Entry Requirements

Find the entry requirements most relevant to you.

• Three-year bachelor's degree from an Australian university, or equivalent, in any area, or
• A minimum of five years of 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): One-plus years of full-time tertiary study in a country from the list of Accepted English-speaking countries.
• IELTS (Academic) Minimum overall score of 6.0 with a minimum of 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).

Outcomes

Career Outcomes

• This degree provides a diverse range of career outcomes with opportunity to advance your profession into any big-data, artificial intelligence or machine learning field. As a graduate, you will become an efficient data scientist, utilising predictive analytics, big data management, big data analysis and modelling, artificial intelligence and machine learning 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 and navigate artificial intelligence and machine learning for the betterment of business.
• Careers with a focus on artificial intelligence may include computer engineering, games development, intelligence analysis, programming and web development. Data science careers can include data scientist, data analyst, data engineer or data 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 course you're enrolled in.
• Depending 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.