Master of Data Science and Artificial Intelligence

Master of Data Science and Artificial Intelligence

POSTGRADUATE

 Transform your career with one of the world's most sought-after skill sets. 

Student type:
Learning mode:
On campus
Entry score:

Not applicable

Duration:
Full-time 2 years
Part-time 4 years
Next intake:
February, July
Location:
Melbourne City
Learning mode:
On campus
Entry score:

See admissions

Duration:
Full-time 2 years
Next intake:
February, July
Location:
Melbourne City

Overview

Designed for career-changers and recent graduates, this degree builds strong foundations in data science and AI with no prior computing background required.

Create, deploy and govern AI-enabled, data-driven solutions for industry challenges. This conversion degree is designed for graduates from any discipline who want to build a successful career in the rapidly growing fields of data science and AI. Whether your background is in business, science, engineering, health, economics or the social sciences, you’ll follow a structured pathway to develop the technical, analytical and strategic capabilities needed to thrive in today's data-driven economy.

Beginning with the foundations you need to progress confidently into the sector, you’ll develop skills in programming, data analysis, computational thinking, AI and the responsible use of technology. As you progress, you’ll learn how to work with data, select and apply appropriate methods, evaluate AI systems, and communicate technical findings to different audiences.

Unlike traditional courses that focus on isolated technical skills, this degree prepares you to work across the entire data and AI lifecycle, from acquiring, managing and analysing data through to designing intelligent systems, deploying AI solutions, and addressing governance, ethics and organisational impact. You’ll gain hands-on experience using contemporary tools, cloud platforms and real-world datasets while learning industry practices such as Data Engineering Pipelines and DataOps, Machine Learning Operations (MLOps), Generative AI and Agentic AI.

Many organisations need people who can do more than use technical tools. They need professionals who can understand the context of a problem, work across disciplines and translate between technical teams, decision-makers and industry specialists. You’ll graduate with a combination of data science, AI and applied problem-solving capabilities, complementing the perspective of your previous field so you can approach problems from more than one direction.

By graduation, you'll have developed a portfolio of practical work that demonstrates your ability to design, build, deploy and govern modern data and AI solutions – providing employers with clear evidence of your technical expertise, professional skills and industry readiness.

Why study data science and AI at RMIT?

Future-focused curriculum

Study cutting-edge technologies, preparing you for the next generation of intelligent, AI-enabled systems.

End-to-end expertise

Master the complete lifecycle from data engineering and analytics to AI deployment, governance and strategy.

Graduate industry-ready

Build practical skills through real-world projects, cloud platforms and authentic assessments.

Choose your specialisation

Data infrastructure

Design and manage scalable data platforms and engineering pipelines.

Build the foundations that power modern data and AI systems. You'll learn to design, manage and optimise scalable data platforms, engineering pipelines and big data environments using industry-standard technologies and DataOps practices. This specialisation prepares you for careers in data engineering, cloud data infrastructure and enterprise-scale analytics, where reliable, high-quality data is essential for AI innovation.

AI systems and applications

Develop, deploy and govern intelligent systems for real-world use.

Develop the knowledge and skills to design, build and deploy intelligent systems that solve complex real-world problems. You'll explore the latest advances in artificial intelligence, including Generative AI, Agentic AI, Deep Learning and intelligent decision-making, while gaining practical experience in developing AI applications using contemporary tools and techniques. This specialisation prepares you for careers in AI engineering, machine learning, intelligent automation and next-generation AI application development.

Data analysis

Transform data into actionable insights using advanced analytical and machine learning techniques.

Develop advanced analytical and statistical expertise in areas such as regression, multivariate analysis, Bayesian statistics, time series forecasting and optimisation, enabling you to tackle complex business and research challenges. This specialisation prepares you for careers in advanced analytics, quantitative modelling and decision intelligence across a wide range of industries.

Data science leadership

Combine technical knowledge with strategy, governance and organisational decision-making to lead data and AI initiatives.

Develop the strategic leadership skills to drive data and AI-enabled transformation in organisations. You'll explore digital strategy, AI leadership, data architecture, governance, ethics, innovation and organisational change, learning how to align technology with business objectives and lead multidisciplinary teams. This specialisation prepares you for leadership roles where you'll shape data-driven strategy, govern responsible AI adoption and deliver sustainable digital innovation.

Details

How you will learn

Learning is grounded in RMIT's Active, Applied and Authentic (AAA) approach, with industry-relevant projects, case studies and practical assessments that mirror professional practice. Throughout the degree, you'll develop advanced technical capability as well as the ethical judgement, communication skills and professional responsibility required to deploy AI safely, transparently and responsibly.

Through hands-on labs, coding exercises, industry case studies, collaborative projects and authentic assessments, you'll apply theory to real-world problems using contemporary datasets, cloud platforms and AI tools. Rather than focusing only on building models, you'll learn how modern AI systems are designed, deployed, monitored and governed in professional environments.

You’ll engage with current research, emerging technologies and contemporary industry practice. Learning activities encourage critical thinking, experimentation, and evidence-based decision making, while authentic projects and capstone experiences provide opportunities to solve complex, real-world challenges.  

By the time you graduate, you'll have developed the advanced technical knowledge, professional judgement and practical experience needed to design and deliver responsible, scalable data science and AI solutions.

How you will be assessed

Assessment is designed to help you progressively build the knowledge, practical skills and professional judgement expected of today's data and AI professionals. As you move through the degree, assessments evolve from developing foundational competencies in programming, statistics and data management to solving complex, real-world challenges in machine learning, AI and intelligent system design. 

Assessment is designed not only to evaluate your technical capability but also your ability to think critically, communicate effectively, collaborate with others, and make ethical and responsible decisions. You'll learn to evaluate alternative approaches, justify technical decisions, and consider issues such as fairness, privacy, governance and the societal impacts of AI. 

Industry connections

The Master of Data Science and Artificial Intelligence has been developed in close partnership with industry to ensure you graduate with the knowledge, skills and experience employers are seeking in today's rapidly evolving AI and data landscape. 

The degree is informed by the RMIT School of Computing Technologies Industry Advisory Committee, comprising senior leaders from industry who provide ongoing advice on emerging technologies, workforce needs and graduate capabilities. Their insights help ensure the curriculum remains current, industry-relevant and aligned with the skills employers value most. 

RMIT also has strong connections with leading technology companies, government agencies, start-ups and organisations across finance, healthcare, retail, manufacturing and consulting. These partnerships contribute to authentic learning experiences, industry-informed curriculum design and opportunities for students to engage with real-world challenges.

Throughout your studies, you'll work on industry-inspired case studies and practical projects that reflect contemporary professional practice, with exposure to the tools, workflows and collaborative practices used by modern data and AI teams. You'll also explore emerging technologies, ensuring your knowledge remains at the forefront of this rapidly changing field. 

The types of classes you have will depend on the course you’re studying. Classes are offered in various formats designed to provide meaningful engagement with staff, industry and peers and provide for access and use of spaces where learning can be applied and active, including an array of specialised equipment.

Most RMIT courses do not include passive large-scale classes such as lectures, instead the content traditionally provided in lectures is made available online. This may be in the form of readings, videos or other on-demand learning materials. This content will also support the basis of interactive learning that takes place in on-campus classes.

The world is constantly changing, and there are universal skills that can help you adapt to the evolving nature of work and global engagement.

As part of your study experience at RMIT, we provide 6 future-focused RMIT Capabilities:

  • Ethical Global Citizens
  • Connected
  • Adaptive
  • Digitally Adept
  • Expert
  • Critically Engaged.

RMIT Capabilities are built into your course as well as some of our extracurricular experiences. They inform the design and delivery of your learning activities and assessments, so by the time you graduate, you’ll be ready to apply these capabilities in your life and work.

Full-time students are expected to attend approximately 16 hours of classes and undertake approximately 24 hours of independent study and research weekly with the majority of classes are delivered during the day.

Full- or part-time study is determined by how many credit points you are enrolled in during the semester. 

If you are a domestic student, you can choose to switch to a part-time study load. This may impact your program duration and tuition fees. Please discuss your study options with your program manager prior to enrolment. International students are required to maintain a full-time study load all times.

Full-time students are expected to attend approximately 16 hours of classes and undertake approximately 24 hours of independent study and research weekly with the majority of classes are delivered during the day.

Important information for international students

International student visa holders can only study full-time.

Course structure and plan

Year 1

Your first year gives you a solid grounding in the core concepts you’ll need, such as programming fundamentals and practical data science. You'll learn the foundational concepts of AI, and gain hands-on experience in the field with real-world tools and applications. 

Year 2

In your second year, you'll deepen your understanding of machine learning, as well as computing research and project preparation. You'll explore your chosen specialisation, allowing you to focus on the areas that match your goals.

Work-integrated learning (WIL)

In this course you'll undertake 3 specific subjects that focus on work-integrated learning (WIL):

Data Science and AI in Practice

In a real or simulated industry setting, you will apply your knowledge of data analytics, machine learning, and data engineering across a full project lifecycle.  

Alongside technical skills, you’ll develop workplace capabilities in teamwork, stakeholder engagement, agile collaboration, version control and documentation, while exploring responsible practices such as data privacy, fairness and ethical AI. This practical experience will build your confidence and prepare you for professional roles in data science and artificial intelligence.

Applied Technology Project

In this subject you will gain hands-on experience developing software in a project team, taking it from inception through to implementation.

You will apply your technical knowledge in a corporate environment and use Agile project management and software delivery methods. As a capstone experience, the Applied Technology Project will help you bring together your learning, respond to industry feedback and build the skills and confidence to move into professional practice.

Professional Practice and Case Studies in Data Science and AI

You will explore how data-driven and intelligent systems are shaping industries including health, finance, transport and security. Using real-world case studies in a simulated workplace, you will develop the skills to frame problems, design solutions, work collaboratively and communicate insights to stakeholders.

You will also examine the legal, ethical, privacy, security and governance responsibilities involved in using data and AI, with feedback from industry practitioners helping you build professional confidence and prepare for advanced project work and a career in data science and artificial intelligence.

Learning outcomes

Upon graduating, you’ll have the knowledge, practical skills and confidence to solve complex problems using data and AI in real-world settings.

You’ll build a strong foundation in programming, statistics, data management and computational thinking before progressing to advanced capabilities in machine learning, AI, data engineering and intelligent systems. Along the way, you'll gain hands-on experience with contemporary technologies including Generative AI, Agentic AI, MLOps, DataOps, cloud platforms and modern AI development tools.

By the time you graduate, you’ll be able to:

  • design, develop and evaluate end-to-end data science and AI solutions for real-world problems
  • build and deploy machine learning and AI applications using industry-standard tools, platforms and workflows
  • manage the complete data and AI lifecycle from data acquisition and engineering through model development, deployment, monitoring and governance
  • analyse complex datasets and transform data into actionable insights that support evidence-based decision making
  • apply emerging AI technologies responsibly, considering ethics, privacy, fairness, transparency and regulatory requirements
  • communicate technical concepts and analytical findings effectively to both technical and non-technical audiences
  • collaborate in multidisciplinary teams using professional software engineering, DataOps and MLOps practices
  • adapt to rapidly evolving technologies and continue learning throughout your career.

Choose a plan below to find out more about the subjects you will study and the course structure.

Master of Data Science and Artificial Intelligence
Program code: MC292

Title
Location
Duration
Plan code
CRICOS
Master of Data Science and Artificial Intelligence
City Campus
Full-time 2 Years, Part-time 4 Years
MC292
Location
City Campus
Duration
Full-time 2 Years, Part-time 4 Years
Plan code
MC292
CRICOS

Career

As AI continues to reshape every industry, employers are looking for professionals who understand not just algorithms, but complete, production-ready AI systems. This degree equips you with the end-to-end knowledge, practical experience and adaptable mindset to become one of those professionals: ready to lead innovation and create impact in the next generation of intelligent, data-driven organisations. 

With expertise spanning the complete data and AI lifecycle, graduates are well positioned to work across industries including technology, finance, healthcare, government, retail, logistics and consulting, helping organisations harness data and AI to drive innovation and informed decision-making.

Potential salaries

Business intelligence analyst

Business intelligence analysts analyse large amounts of data to inform and improve business strategies. The average salary in Australia for a business intelligence analyst is $115,000*.

Data scientist

Data scientists use data to identify trends and provide insights into real-world problems. The average salary in Australia for a data scientist is $125,000*.

Data engineer

Data engineers explore new ways to interpret and manage data and achieve business goals. The average salary in Australia for a data engineer is $135,000*.

*Source: Seek.com.au 2026

Entry requirements and admissions

You need to satisfy all of the following entry requirements to be considered for entry into this degree.

  • Successful completion of an Australian bachelor's degree (or international equivalent) in any discipline with a GPA of at least 2.0 out of 4.0;
    or
  • A minimum of 5 years of relevant work experience in information security, programming (web, application, database); software engineering; system, functional or business analysis; information, system or enterprise architecture; ICT management; administration (network, systems); support (desktop, helpdesk, system); web design/media; business information systems or information systems.

International qualifications are assessed for comparability to Australian qualifications according to the Australian Qualifications Framework (AQF).

If you wish to have industry or employment experience assessed as part of meeting the entry requirements you will need to provide a detailed CV/resume listing previous positions, dates of employment and position responsibilities; a statement from your employer confirming these details (or contact details of employer so RMIT can seek confirmation); and evidence of any relevant professional development undertaken.

There are no prerequisite subjects required for entry into this qualification.

A selection task is not required for entry into this qualification.

You must meet the University's minimum English language requirements to be eligible for a place in this course.

You need to satisfy all of the following requirements to be considered for entry into this course.

There are no prerequisite subjects required for entry into this qualification.

A selection task is not required for entry into this qualification.

To study this course you will need to complete one of the following English proficiency tests:

  • IELTS (Academic): minimum overall band of 6.5 (with no individual band below 6.0)
  • TOEFL (Internet Based Test - IBT) for Australia: minimum overall score of 79 (with minimum of 13 in Reading, 12 in Listening, 18 in Speaking and 21 in Writing)
  • Pearson Test of English (Academic) (PTE (A)): minimum score of 58 (with no communication band less than 50)
  • Cambridge English: Advanced (CAE): minimum of 176 with no less than 169 in any component.

Note: RMIT does not accept scores from 'at-home' or 'online' testing.

For detailed information on English language requirements and other proficiency tests recognised by RMIT, visit English language requirements and equivalency information.

Don't meet the English language test scores? Complete an English Language Pathways (Academic English) Advanced at RMIT University Pathways (RMIT UP).

Additional information

Non-academic abilities you'll need to complete this course

The following information outlines the tasks you will be required to undertake during professional experience placement and on-campus learning activities.

The non-academic abilities listed are provided for your information only and are not entry requirements.

By understanding the types of activities you'll participate in, you can:

  • understand more about the course
  • determine if you may need support during your studies
  • make an informed decision about whether the course is suitable for you.

Adjustments

If there are any activities outlined which may be difficult for you to undertake, there is a range of adjustments to your study conditions available to enable and support you to demonstrate these abilities.

Please contact the Equitable Learning Services (ELS) team to discuss any adjustments you may require. To receive learning adjustments, you need to register with ELS.

If you are living with disability, long-term illness and/or a mental health condition, we can support you by making adjustments to activities in your course so that you can participate fully in your studies.

The University considers the wellbeing and safety of all students, staff and the community to be a priority in academic and professional experience placement settings.

Pathways and further study

You can gain entry to this master's degree from a range of RMIT undergraduate courses, if you meet the entry requirements.

Credit, recognition of prior learning, professional experience and accreditation from a professional body can reduce the duration of your study by acknowledging your earlier, relevant experience.

Credit and exemptions will be assessed consistent with the principles of the RMIT Credit Policy.

Upon successful completion of this master's degree, you may be eligible to undertake further studies in related courses at RMIT University, including MR221 Master of Computer Science (Research) and DR221 PhD in Computer Science, subject to each degree's entry requirements.

You can gain entry into this degree from a range of RMIT undergraduate degrees.

Credit

Credit may reduce the duration of your study by acknowledging your earlier, relevant study experience.

When you are submitting an application, please indicate that you want to be considered for credit and provide detailed course syllabus (also known as course outline), outlining volume of learning, course content and weekly topics, learning objectives/outcomes, assessment types and their weightings, and reference to the learning resources such as prescribed textbooks and recommended readings.

Credit and exemptions will be assessed consistent with the principles of the RMIT Credit Policy.

Upon successful completion of this degree, you may be eligible for entry into an RMIT Master by Research or Doctoral (PhD) degree.

Fees

This degree has full-fee places, with a limited number of Commonwealth supported places (CSP). 

Government financial assistance is available to eligible students regardless of the type of place you enrol in.

2027 indicative fees

  • Full-fee places: AU$38,400 (2027 annual)

Commonwealth supported places

  • 2027 Commonwealth supported places (CSP) range from AU$4,908 to AU$18,025*. 

Additional expenses

  • Student services and amenities fee (SSAF): AU$386 maximum fee for 2027*.
  • Other items related to your program, including field trips, textbooks and equipment.

Annual fee adjustment*

Amounts quoted are indicative fees per annum, and are based on a standard year of full-time study (96 credit points). A proportionate fee applies for more or less than the full-time study load.

*Fees are adjusted on an annual basis and these fees should only be used as a guide.

Defer your payment

This program is offered on a full-fee paying basis only. If you are offered a place, you will need to pay the full tuition costs of your program. However, eligible students (such as Australian citizens or holders of an Australian permanent humanitarian visa) may apply to defer payment of some or all of their tuition fees via the Commonwealth Government’s FEE-HELP loan scheme.

Paying your fees and applying for refunds

For information on how to pay your fees or how to apply for a refund, please see Paying your fees and applying for refunds.

If you are offered a full-fee place, you will need to pay the full tuition costs of your degree. However, eligible students (such as Australian citizens or holders of an Australian permanent humanitarian visa) may apply to defer payment of some or all of their tuition fees via the Commonwealth Government’s FEE-HELP loan scheme.

If you are offered a Commonwealth supported place, your tuition fees are subsidised by the Australian Government.

Your share of the fee (student contribution) is set on an annual basis by the government and is determined by the discipline areas (bands) of your individual enrolled courses, not the overall program.

How much can I expect to pay for my Commonwealth supported place?

The Australian Government has introduced changes to university funding and student contribution fees under its Job-ready Graduates Package

The fees in the table below apply to students who commence their degree in 2027. Fees for continuing students are available at fees for Commonwealth supported students.

Each subject (course) falls into a band. The band determines the student contribution amount for the subject.

Amounts listed in the table below are based on a standard, full-time study load (96 credit points per year) with all subjects in the same band. A proportionate fee applies for more or less than the full-time study load or for enrolment in subjects from a combination of bands.

You can learn how to calculate your exact tuition fees for units from different bands at Fees for Commonwealth supported students.

Maximum student contribution amount for Commonwealth supported places in 2027 for commencing students

Student contribution band by subject

Maximum annual student contribution amount (per EFTSL) in 2027

Education, Postgraduate Clinical Psychology, English, Mathematics, Statistics, Nursing, Indigenous and Foreign Languages, Agriculture $4,908 per standard year
$613 per standard (12 credit point) course
Allied Health, Other Health, Built Environment, Computing, Visual and Performing Arts, Professional Pathway Psychology, Professional Pathway Social Work, Engineering, Surveying, Environmental Studies, Science, Pathology $9,880 per standard year
$1,235 per standard (12 credit point) course
Dentistry, Medicine, Veterinary Science $14,046 per standard year
$1,755 per standard (12 credit point) course
Law, Accounting, Administration, Economics, Commerce, Communications, Society and Culture $18,025 per standard year
$2,253 per standard (12 credit point) course

Student Learning Entitlement

On 1 January 2022, the Government implemented the Student Learning Entitlement (SLE).

  • The SLE allows students 7 years of full-time subsidised study in Commonwealth Supported Places (CSP).
  • Your total SLE amount will be reduced in accordance with your overall study load in a CSP. 
  • Once you have utilised all your SLE, you can no longer study in a CSP.

In addition to tuition fees, you will be charged an annual student services and amenities fee (SSAF), which is used to maintain and enhance services and amenities that improve your experience as an RMIT student.

The SSAF is calculated based on your enrolment load and the maximum fee for 2027 is $386.

You may also be required to purchase other items related to your course, including field trips, textbooks and equipment. These additional fees and expenses vary from course to course.

FEE-HELP loans

Eligible students (such as Australian citizens or holders of an Australian permanent humanitarian visa) may apply to defer payment of some or all of their tuition fees via the Commonwealth Government’s FEE-HELP loan scheme.

SA-HELP Loans

You may be eligible to apply to defer payment of the Student services and amenities fee (SSAF) through the SA-HELP loan scheme. If you use SA-HELP, the amount will be added to your accumulated HELP debt.

How does a HELP loan work?

If your FEE-HELP and/or SA-HELP loan application is successful, the Australian Government will pay RMIT, on your behalf, up to 100% of your fees. This amount will become part of your accumulated HELP debt.

You only start repaying your accumulated HELP debt to the Australian Government once you earn above the minimum income threshold for repayment, which is set each year by the Australian Government (this also applies if you are still studying). The Australian Taxation Office (ATO) will calculate your compulsory repayment for the year and include this on your income tax notice.

For more information about loan repayment options see Commonwealth assistance (HELP loans) or Study Assist.

You may be eligible to apply for income tax deductions for education expenses linked to your employment.

See the Australian Taxation Office (ATO) for more information.

RMIT awards more than 2000 scholarships every year to recognise academic achievement and assist students from a variety of backgrounds.

Additional costs

In addition to tuition fees you also need to pay for:

You also need to account for your living expenses. Estimate the cost of living in Melbourne.

Student Services and Amenities Fee (SSAF)

In addition to tuition fees, you will be charged an annual student services and amenities fee (SSAF), which is used to maintain and enhance services and amenities that improve your experience as an RMIT student. The SSAF is calculated based on your enrolment load and the maximum fee for 2027 is $386. 

How your fees are calculated

Find out more details about how fees are calculated and the expected annual increase.

Applying for refunds

Find information on how to apply for a refund as a continuing international student.

RMIT awards more than 2000 scholarships every year to recognise academic achievement and assist students from a variety of backgrounds.

Frequently Asked Questions (FAQs)

Looking for answers or more general information?

Use our Frequently Asked Questions to learn about the application process and its equity access schemes, find out how to accept or defer your offer or request a leave of absence, discover information about your fees, refunds and scholarships, and explore the various student support and advocacy services, as well as how to find out more about your preferred program, and more.

This course is not available for international students intending to study on a student visa.

Information for international students

Sorry, this course is not available for international students intending to study on a student visa. If you hold a different visa type, you may be eligible. Please contact Study@RMIT for more information.

 

Information for local students

If you are a local student please select 'switch to local' below to view the full course information.

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RMIT University acknowledges the people of the Woi wurrung and Boon wurrung language groups of the eastern Kulin Nation on whose unceded lands we conduct the business of the University. RMIT University respectfully acknowledges their Ancestors and Elders, past and present. RMIT also acknowledges the Traditional Custodians and their Ancestors of the lands and waters across Australia where we conduct our business - Artwork 'Sentient' by Hollie Johnson, Gunaikurnai and Monero Ngarigo.

Learn more about our commitment to Aboriginal and Torres Strait Islander peoples