Graduate Certificate in Data Analytics

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 credit points from the following subjects.

• Mathematical Statistics
• Stochastic Processes
• Survival Analysis
• Infrastructure for Data Analytic
• Deep Learning Through Neural Networks
• Statistical Learning and Regression Models
• Modern Machine Learning Models
• Advanced Statistical Learning Models
• Advanced Econometrics

General electives

Students must choose 10 credit points of postgraduate subjects from across the university that are available as general electives.

Entry requirements

Successful completion of a recognised Bachelor's degree (or equivalent qualification) in any field.

English language requirements

Bond’s programs are taught and assessed in English, so depending on your educational background and citizenship, you may need to provide evidence that your English language ability meets the university’s requirements. This may include submitting results from an approved English language test taken in the past two years – the required results for the most common approved tests are listed below. There are other ways to demonstrate English language proficiency and gain entry into the program, including evidence of prior study in English or other recognised qualifications. If your qualification does not meet the English language requirements, you will need to supply a valid English proficiency test result 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)

Contact the university or visit its website for more information.

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

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 2026: $27,200 (domestic full-fee paying place).

Student annual fees may vary in accordance with:

• 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.

You may also need to pay the student services and amenities fee.

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 course.