Master of Data Science at Griffith University

The Griffith University Master of Data Science develop skills in machine learning, analytics, statistics, and large-scale data interpretation. Graduates are well positioned for jobs in data science, machine learning, analytics, and data engineering.

Study modes: Online, Nathan, and Gold Coast
Completion times: 2 years, 1.5 years, or 1 year
Key areas: Machine learning, analytics, statistics, and big data
Suitable for: Career changers and IT professionals
Graduate employment: 91.7% full-time employment
Academic calendar: Trimester structure

Why Students Choose Griffith Data Science

The Griffith University Master of Data Science offers online study, on-campus study, and accelerated completion pathways. Students with prior IT qualifications or industry experience may be able to reduce the duration of the degree.

The course suits several types of students:

Career changers entering data and analytics
IT professionals seeking postgraduate qualifications
Working professionals needing online flexibility
Students wanting accelerated completion pathways

Graduate Outcomes for Griffith Computing

Graduate outcomes for Griffith University’s Computing & Information Systems (Postgraduate) study area are strong overall. Recent survey data shows results above national averages for satisfaction, employment, and salary.

Outcome	Griffith University	National Average
Overall satisfaction	81.4%	73.8%
Full-time employment	91.7%	85.8%
Median salary	$110,000	$104,400

Source: Course Experience Questionnaire and Graduate Outcomes Survey. Updated: 28 May 2026.

Graduate outcomes across Griffith University’s postgraduate computing area are above national averages.

Full-time employment is 91.7% compared with a national average of 85.8%.
Overall satisfaction is 81.4% compared with 73.8% nationally.
Median salary is $110,000 compared with a national average of $104,400.

Note that the graduate outcomes apply to Griffith University’s Computing & Information Systems (Postgraduate) study area rather than exclusively to the Master of Data Science course.

Accelerated Data Science Pathways

The Griffith University Master of Data Science can be as short as one year for professionals with industry experience. A two-year timeframe applies if you lack experience and a relevant degree.

Pathway	Typical Requirement	Duration
Standard entry	Any bachelor degree	2 years
Related discipline	IT or computing-related degree	1.5 years
Advanced standing	Related degree plus 5 years experience	1 year

Related disciplines include data science, computer science, information technology, cyber security, and information systems. Relevant industry experience may include work as a data analyst, data scientist, data engineer, or systems engineer.

Technical Skills in Data Science

Students in the Griffith University Master of Data Science build skills and knowledge in machine learning, data analytics, statistics, and big data analysis.

You learn how to work with large datasets and computational analysis methods linked to areas such as data science, machine learning, analytics, and data engineering.

Trimester Starts and Subject Planning

Griffith uses a trimester system. The program commences in Trimester 1 and Trimester 2.

Before enrolling, it would be sensible to confirm the study plan for your preferred pathway and intake. Some IT and computing subjects may not run every trimester, which can affect sequencing.

Recognition of Prior Learning

Griffith University emphasises Recognition of Prior Learning (RPL). Potential credit sources include prior university study, professional experience, workplace learning, and volunteer or community experience.

For experienced IT professionals, RPL can reduce cost and study duration. The uni also maintains a credit precedent database for past decisions, which may help students estimate likely credit outcomes before applying.