RMIT University

Master of Analytics

  • Delivery: Face to Face
  • Study Level: Postgraduate
  • Duration: 24 months
  • Course Type: Master's

Become a specialist in analytics and build on skills in computer science, engineering and business.

Course overview

The Master of Analytics builds on the tradition of statistics and operations research, bringing together tools and expertise from computer science, engineering and business.

This blend of disciplines makes analytics unique in its capacity to solve critical real-world problems. You will learn how to use data to make informed decisions that make significant contributions to the success of organisations, which provides a rewarding and valued career path.

This degree allows you to choose from a diverse range of electives combined with a strong core of statistics and operations research.

Key facts

Delivery
Face to Face
Course Type
Master's
Duration
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Can be studied part time
24 months (Full time)
Price Per Unit
From $4,440
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The estimated per-unit fee is calculated using the annual average first-year fee. It is based on a full-time study load of 96 credit points (eight subjects) per year.
Campus
Melbourne CBD
Intake
July, 2026
Units
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You may be required to complete 0 credit point units throughout your course. The university will confirm this as part of your enrolment.
16
Fees
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FEE-HELP loans are available to assist eligible full-fee paying domestic students with the cost of a university course.
FEE-HELP

What you will study

To graduate, you must complete the following. Each course (subject) is valued at 12 credit points.

Year One of the Program

Complete the following courses (subjects):

  • Applied Analytics
  • Database Concepts
  • Data Wrangling

AND

Complete up to 24 credit points (two courses or subjects) from the following. Note: if you choose 24 credit points from this list, you may only choose 12 credit points (one course or subject) from the second list.

  • Essential Mathematics
  • Data Visualisation and Communication
  • Machine Learning
  • Time Series Analysis

AND

Complete up to 24 credit points (two courses or subjects) from the following. Note: if you chose 24 credit points from the previous list, you may only choose 12 credit points (one course or subject) from this list.

  • Optimisation for Decision Making
  • Applied Bayesian Statistics
  • Analysis of Categorical Data
  • Design and Analysis of Experiments
  • Forecasting
  • Multivariate Analysis Techniques
  • Regression Analysis
  • Statistical Inference
  • Statistics of Quality Control and Performance Analysis
  • Stochastic Processes and Applications
  • Game Theory and Its Applications
  • Advanced Optimisation
  • Questionnaire and Research Design
  • System Dynamics
  • Sports Analytics
  • Introduction to Statistical Computing
  • Statistical Data Science

AND

Complete 24 credit points (two courses or subjects) from the Science Options list.

Year Two of the Program
Science Options List

Entry requirements

Academic requirements

Applicants must have one of the following:

  • A bachelor's degree.
  • At least 10 years of relevant work experience.

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.

English language requirements

You must meet the university's minimum English language requirements to be eligible for a place in this program. Contact the university for more details.

Recognition of Prior Learning

You may be able to get credit for your course based on prior formal, non-formal or informal learning. To apply, you will need to provide supporting documentation outlined by the university. Contact the university for more information.

Outcomes

Learning outcomes

Upon successful completion of this program, you will have a comprehensive understanding of and technical competence in fundamental and applied mathematical and statistical knowledge, methodologies and modern computational tools.

You will be able to expertly source and evaluate data, paying particular mind to its diverse and evolving social, political and cultural dimensions. Your understanding of the complexity of various mathematical and statistical models will enable you to conduct research on complex industry issues, critically analyse, consolidate and synthesise your findings and finally, design bespoke solutions to them.

Essential skills in problem solving, decision-making, leadership, collaboration and project planning will ensure you are able to practice in a range of roles, teams and organisations, where you will take ownership of your work, resolve conflicts and deliver value to the business.

Career outcomes

Graduates are employed by a variety of scientific, commercial and government enterprises, most commonly as data scientists, statisticians, business analysts, consultants, modellers and researchers.

Fees and FEE-HELP

Estimated first-year tuition fee in 2026: $35,520 (domestic full-fee paying place).

Additional expenses:

  • Student services and amenities fee (SSAF): $373 maximum fee for 2026.
  • Other items related to your program include field trips, textbooks and equipment.

All costs are calculated using current rates and are based on a study load of 96 credit points (normally eight units) per year.

A student’s fee may vary depending on:

  • The number of subjects studied per term.
  • The choice of major or specialisation.
  • Choice of subjects.
  • Credit from previous study or work experience.
  • Eligibility for government-funded loans.

Student fees shown are subject to change. Contact the university directly to confirm.

FEE-HELP loans are available to assist eligible full-fee paying domestic students with the cost of a university program.