Master of Data Science (MADS)

Back to top Program aims With the popularity of social media and the wide spread use of the Internet, enormous amounts of data of various types are generated at all times.

The Master of Data Science is designed to provide an opportunity for graduates from all disciplines to gain advanced skills and knowledge in handling data more commonly known as Big Data, as well as producing and interpreting data analytics.

The aim of this program is to provide students with a career path in Data Science and an opportunity for advancement in their career.

Admission requirements

To be eligible for admission, applicants must satisfy the following requirements:

• Completion of an Australian university three year Bachelor degree in any area, or equivalent OR
• A minimum of five years’ professional work experience equivalent to a qualification at AQF Level 7.
• English Language Proficiency requirements for Category 2.

All students are required to satisfy the applicable English language requirements.

If students do not meet the English language requirements they may apply to study a University-approved English language program. On successful completion of the English language program, students may be admitted to an award program.

Program objectives

On completion of the program students should 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.