Bond University
Graduate Certificate in Data Analytics
- Delivery: Face to Face
- Study Level: Postgraduate
- Duration: 4 months
- Course Type: Graduate Certificate
Explore applications in nearly all aspects of quantitative endeavours and information management with this course.
Course overview
Data analytics has become one of the highest growth areas of academic and commercial practice. With applications in nearly all aspects of quantitative endeavours and information management, a skillset in analytics, statistical and machine learning is highly valued and sought after. As such, there is a high demand for pathways for developing data analytics skills, both as a primary and a professional transition education pathway.
Bond's Graduate Certificate in Data Analytics is AACSB and EQUIS accredited.
Key facts
May, 2026
What you will study
You are required to complete a total of 40 credit points. This is comprised of 30 credit points for data analytics options and 10 credit points for general electives from across the university.
Data analytics options
Students must choose 30 CP from the following subjects.
- Mathematical Statistics (10 credit points)
- Stochastic Processes (10 credit points)
- Survival Analysis (10 credit points)
- Infrastructure for Data Analytics (10 credit points)
- Deep Learning Through Neural Networks (10 credit points)
- Statistical Learning and Regression Models (10 credit points)
- Modern Machine Learning Models (10 credit points)
- Advanced Statistical Learning Models (10 credit points)
- Advanced Econometrics (10 credit points)
General electives
Students must choose 10 credit points of postgraduate subjects from across the university that are available as general electives.
Entry requirements
Completion of a recognised bachelor's degree (or equivalent qualification) in any field is required for this course.
You may use prior work experience to apply for entry into this program. To do so, you will need to provide documentation of your employment history, including a statement from your employer about your position, time in the role and a brief overview of the role you performed.
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.
Outcomes
Career outcomes
Graduates may pursue roles such as:
- Data Scientist
- Business Analyst
Learning outcomes
- Identify appropriate data analytic techniques to address statistical problems.
- Demonstrate proficiency in data visualisation and applying and interpreting statistical models and machine learning algorithms to solve problems in various contexts.
- 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: $22,790 (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.