Master of Data Science
Interdisciplinary master’s programme combining computer science, statistics, and domain expertise to extract insights from big data.
Best for:Best for graduates or professionals with a background in computing, science, engineering, or statistics seeking to specialise in data analysis and computational techniques for big data applications.
Overview
The Master of Data Science at RMIT University equips students with the skills to manage and analyse vast datasets from diverse sources like social media, sensors, and transactions. This programme integrates computational techniques, statistical methods, and domain-specific knowledge to derive actionable insights for businesses, governments, and research. Graduates will develop expertise in handling big data, enabling them to drive innovation, improve decision-making, and advance discoveries. The curriculum emphasises hands-on computational skills and interdisciplinary collaboration, preparing students for careers in data-driven industries. Applicants should have a strong foundation in computing, science, engineering, health, or statistics, with proficiency in programming and statistical analysis.
What you'll do
- Develop advanced computational and statistical skills to analyse large datasets from diverse sources.
- Apply data science techniques to derive meaningful insights for business, government, and research applications.
- Collaborate across disciplines to integrate domain expertise with computational methods.
- Work on real-world projects involving big data, including social media, sensor networks, and transactional data.
- Develop proficiency in programming languages and tools essential for data processing and analysis.
- Engage in interdisciplinary research and contribute to innovative solutions in data-driven fields.
Requirements
Degree required: Australian bachelor’s degree in computing, science, engineering, health, or statistics with a GPA of at least 2.0 out of 4.0, or equivalent. Alternatively, an Australian bachelor’s degree with a GPA of at least 2.0 out of 4.0 and relevant completed courses in programming and statistics, or a minimum of three years of current, relevant work experience as a programmer, statistician, or equivalent.
Language: English proficiency (not explicitly stated but implied for academic programme).
Instruction: English
- Proven academic background in computing, science, engineering, health, or statistics.
- Completed courses in programming and statistics, or equivalent professional experience.
- Minimum three years of relevant work experience as a programmer, statistician, or equivalent (if no formal degree in the field).
- Basic proficiency in programming languages (e.g., Python, R).
- Understanding of statistical analysis and data interpretation.
- Australian bachelor’s degree or equivalent with a minimum GPA of 2.0 out of 4.0.
- Alternative eligibility via relevant coursework or professional experience.
Funding & terms
Programme and admissions
Admissions not verified
A catalogue listing does not mean applications are open or funding is guaranteed. Check the source for your intake.
- Intake
- Not confirmed by the source
- Duration
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- Teaching language
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- Taught / research mode
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- Study mode
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- Campus
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- Prerequisites
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- Application instructions
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- Tuition
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How to apply
Deadline: unknown
Applicants should apply directly through RMIT University’s official postgraduate application portal. Ensure all required documents are submitted, including academic transcripts, proof of English proficiency (if applicable), and a personal statement outlining your interest and qualifications for the programme.
- Academic transcripts
- Proof of English proficiency (if required)
- Personal statement or statement of purpose
- Curriculum Vitae (CV)
- Proof of relevant work experience (if applicable)
Create a free profile to unlock your personal match score, the full requirements, funding details and how to apply — in English or Persian.