Course Overview

About This Course

The Master of Data Science (MDS) provides students with comprehensive mastery of all aspects of knowledge and skills related to data science and an opportunity to focus on specialised technical, theoretical or managerial skills through the choice of one specialisation. The MDS places an emphasis on professional practice, effective communication, and project management using technical and non-technical approaches. Students will acquire extensive and deep knowledge to enable them to successfully design, implement and manage data science based solutions in complex real-world applications. Students will become confident in utilising the latest technologies in the data science, significantly enhancing their prospects in career development or entrepreneurship. Students can nominate a specialisation that allows them to fulfil their own particular interests, their own industry needs, or their own career goals. In particular, students may choose to gain expertise in Artificial Intelligence if they choose not to proceed with the default specialisation. The MDS is designed for students who have limited experience in, or have been seeking a qualification in, data science. The degree also caters for candidates who already have a sound data science background but wish to update and develop their knowledge and skills to keep pace with the rapid changes in technology and the business opportunities related to the latest advances in data science.

Eligibility

Entry Requirements

Requirements

An AQF Level 7 qualification (such as an approved three-year undergraduate degree) that includes study areas requiring quantitative reasoning and analysis, with a minimum GPA of 4.5; or
Completion of the SPI Graduate Diploma of Data Science or SPI Graduate Certificate in Data Science (Eligible units may be credited towards the Master of Data Science in accordance with SPI's Academic Credit and Recognition of Prior Learning Policy); or
Other qualifications combined with relevant work or professional experience may be considered on a case-by-case basis.
Qualifications presented for admission should have been obtained no more than 5 years prior to the commencement of the program at SPI. Applicants with qualifications older than 5 years are required to provide a statement demonstrating: the continued relevance and applicability of the student's prior knowledge to the proposed study at SPI, or engagement in continuous learning or professional development since obtaining the last qualification, or any relevant work experience related to the field of study.
English as a First Language – Applicants must hold citizenship or long-term residency (minimum of 10 years) in an English-speaking country recognised by SPI and have completed secondary or higher education in that country.
English Not as a First Language (Domestic) – Applicants are required to provide a valid English proficiency certificate as proof of English language competency.
International applicants must meet one of the following English language requirements:
- IELTS (Academic): Overall 6.5, with no band less than 6.0
- PTE Academic: Overall 58, with no sub-score less than 50
- TOEFL iBT: Overall 79, including minimum scores of Writing: 21, Reading: 13, Listening: 12, Speaking: 18
- TOEFL PBT: Overall 550, including Writing 4.5
- Other English language tests recognised as equivalent to IELTS Academic 6.5
English test results must be valid and taken within three (3) years prior to course commencement.
Students must be at least the age of 18 upon course commencement.

Career & Study Pathways

Where this takes you

Career Opportunities

Software Developer (Average salary $75,000 – $110,000), Cybersecurity Analyst (Average salary $80,000 – $120,000), UX/UI Designer (Average salary $75,000 – $115,000), Data Analyst (Average salary $70,000 – $105,000), Systems Analyst (Average salary $85,000 – $125,000), AI Specialist (Average salary $95,000 – $150,000).

Course Content

Units of Competency

All Units21 units

MDS601

Programming Foundations for Data Science

Core unit covering programming foundations required for data science practice.

MDS602

Mathematical Foundations for Data Science

Core unit covering mathematical foundations required for data science practice.

MDS603

Data Science Methodology

Core unit covering data science methodology.

MDS604

Database Systems and Infrastructure

Core unit covering database systems and infrastructure.

MDS605

Machine Learning and Data Mining

Core unit covering machine learning and data mining.

MDS606

Data Science Research and Ethics

Core unit covering research and ethics in data science.

MDS607

Artificial Intelligence and Innovation

Core unit covering artificial intelligence and innovation.

MDS608

Professional Practice

Core unit covering professional practice.

MDS650

Data Science Capstone Project

Capstone project allowing students to apply skills to real-world data challenges (18cp). Select one of MDS650 or MDS651.

MDS651

Industrial Experience Project

Industry experience project allowing students to apply skills to real-world data challenges (18cp). Select one of MDS650 or MDS651.

MDS611

Data Visualization and Tools

Specialisation core unit focusing on data visualisation.

MDS612

Big Data Infrastructure and Processing

Specialisation core unit focusing on big data infrastructure and processing.

MDS615

Cloud Computing and Application Development

Specialisation core unit focusing on cloud computing and application development.

MDS609

Business Intelligence and Analytics

Elective unit covering business intelligence and analytics.

MDS610

Decision Making for Analytics

Elective unit covering decision making for analytics.

MDS614

Unstructured Data and Computer Vision

Elective unit covering unstructured data and computer vision.

MDS617

Mixed Reality

Elective unit covering mixed reality.

MDS618

Autonomous Theory and Programming Robots

Elective unit covering autonomous theory and programming robots.

MDS619

Natural Language Processing and Applications

Elective unit covering natural language processing and applications.

MDS621

Game Designing

Elective unit covering game designing.

MDS622

Foundations and Applications of Fin-Tech

Elective unit covering foundations and applications of financial technology.

Common Questions

Frequently Asked Questions

How many credit points are required to complete the Master of Data Science, and how is the course structured?

The Master of Data Science is a 2-year AQF Level 9 qualification comprising 96 credit points. It includes three streams: a Core Units Stream (66 credit points) covering 9 core units plus a capstone or industry experience project, a Specialisation Core Units Stream (18 credit points) with 3 units in data visualisation, big data infrastructure, and cloud computing, and an Elective Units Stream (12 credit points) where students choose 2 units from a range of advanced topics.

Can I choose a specialisation within the Master of Data Science?

Yes, students can nominate a specialisation that allows them to fulfil their own particular interests, their own industry needs, or their own career goals. In particular, students may choose to gain expertise in Artificial Intelligence if they choose not to proceed with the default specialisation.

What are the English language requirements for international applicants?

International applicants must meet one of the following: IELTS (Academic) Overall 6.5 with no band less than 6.0; PTE Academic Overall 58 with no sub-score less than 50; TOEFL iBT Overall 79 with minimum scores of Writing 21, Reading 13, Listening 12, Speaking 18; TOEFL PBT Overall 550 including Writing 4.5; or other English language tests recognised as equivalent to IELTS Academic 6.5. English test results must be valid and taken within three years prior to course commencement.

What intake dates are available for the Master of Data Science?

The Master of Data Science has three intake dates: 09 March 2026, 06 July 2026, and 12 October 2026.

Do students at SPI receive any professional membership benefits while studying the Master of Data Science?

Yes, all SPI students can access a complimentary membership with the Australian Computer Society (ACS) — Australia's largest tech association — giving students access to industry connections, career resources, and professional development opportunities while they study.

Application

How to Apply

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Step 02

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Step 03

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Master of Data Science