Bond University
Master of Data Analytics
- Delivery: Face to Face
- Study Level: Postgraduate
- Duration: 16 months
- Course Type: Master's
Equips students with advanced knowledge and techniques that enhance business decision-making and can be applied across a vast range of industry sectors.
Course overview
The Master of Data Analytics is delivered via smaller classes providing personalised support and unparalleled access to Bond University's Bond Fin Tech Hub and Bloomberg data-sourcing terminals. Focus within this program is on strategically sound recommendations and data-driven business decisions.
As a Bond Business School student, you'll have access to exclusive facilities, including the Bond FinTech Hub, where you can gain Bloomberg certification, as well as the Centre for Data Analytics, offering unparalleled opportunities to work with experts in the field. Through the program’s comprehensive curriculum, you will be prepared to meet the growing demand for data-driven expertise and make a substantial impact in your chosen industry.
The program's flexible structure allows students to specialise in key areas such as Accounting Analytics, Economic Modelling, Health System Analytics, Marketing Analytics, Psychometrics, Quantitative Finance or Sport Analytics.
Key facts
January, 2026
September, 2026
What you will study
To complete the Master of Data Analytics, you must fulfil 120 credit points (CP).
Students must complete the following eighty credit points (80CP) of subjects.
- Data Science (10CP)
- Infrastructure for Data Analytics (10CP)
- Deep Learning Through Neural Networks (10CP)
- Statistical Learning and Regression Models (10CP)
- Applied Data Analytics Project (10CP)
- Modern Machine Learning Models (10CP)
- Linear Models and Applied Econometrics (10CP)
- Quantitative Methods (10CP)
Entry requirements
Successful completion of a recognised Bachelor degree (or equivalent qualification) in any field.
English language proficiency requirements
Bond's programs are taught and assessed in English, so depending on your educational background and citizenship, you may be required to provide evidence that your English language ability meets our requirements. This may include submitting results from an approved English Language Test taken in the past two years - you can see the required results for the most common approved tests below. There are other ways to demonstrate English language proficiency and gain entry into this program, including demonstrating prior study in English, or other qualifications. If your qualification does not meet the English language requirements then you will need to provide an English proficiency test for admission.
- International English Language Testing System (IELTS) Academic Overall score 6.5 with no sub score less than 6.0.
- Pearson Test of English (PTE) Academic Overall score 58 with no Communicative Scores below 50.
- Test of English as a Foreign Language Internet-Based Test (TOEFL iBT) Overall score 79 (no scores below 21 in Writing, 18 in Speaking, and 16 in Reading and Listening).
Recognition of Prior Learning
If you have completed previous tertiary studies, you may be able to gain credit for previous subjects. To apply, you will need to submit your academic transcripts to the Office of Future Students, including detailed subject outlines or course descriptions for each relevant subject. Contact the university for more information.
Outcomes
Career outcomes
- Business analyst
- Data scientist
- Statistical consultant
Learning outcomes
- Identify appropriate data sources and associated analytic techniques to address statistical problems and develop creative and flexible data-based solutions to industry problems.
- Demonstrate proficiency in data visualisation and the application and interpretation of statistical models and machine learning algorithms to solve problems in a variety of contexts and wide range of business disciplines and beyond.
- Perform basic computational and programming tasks associated with the application of data analytics.
- Interpret the output of data analytic models and undertake appropriate diagnostic procedures to assess the appropriateness of the chosen model for the data being analysed.
- Communicate the results of technical analysis to non-technical audiences.
Fees and FEE-HELP
Indicative total program fee in 2025: $66,560 (domestic full-fee paying place)
Indicative semester program fee in 2025: $16,640 (domestic full-fee paying place)
A student’s annual fee may vary in accordance with:
- The number of units studied per term.
- The choice of major or specialisation.
- Choice of units.
- Credit from previous study or work experience.
- Eligibility for government-funded loans.
Student fees listed provide an indicative cost only. Fees are subject to change on an annual basis and will be charged at the appropriate fee for the year of enrolment. 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 course.