Program Requirements
The Master of Applied Data Analytics requires the completion of 72 units, which must consist of:
42 units from completion of the following compulsory courses:
COMP6240 Relational Databases
COMP6730 Programming for Scientists
COMP8430 Data Wrangling
SOCR8201 Asking the Right Questions: Designing Effective Data Collection
SOCR8202 Using Data for Monitoring and Evaluation
STAT7038 Regression Modelling
STAT7055 Introductory Statistics for Business and Finance
A minimum of 6 units from completion of courses from the following list:
STAT6026 Graphical Data Analysis
STAT8130 Generalised Linear Modelling
A minimum of 6 units from completion of courses from the following list:
COMP8410 Data Mining
STAT8140 Statistical Learning
A maximum of 18 units from completion of the following courses:
Business and Management:
INFS8210 Business Analytics for Managers
MGMT7250 Evidence-Based Management
Computer Science:
COMP6490 Document Analysis
COMP6670 Introduction to Machine Learning
COMP8600 Statistical Machine Learning
COMP8880 Computational Methods for Network Science
Social Science:
SOCR8002 Survey Data Analysis
SOCR8006 Online Research Methods
SOCR8010 Advanced Survey Data Analysis
SOCR8082 Social Research Practice
SOCR8203 Advanced Techniques in the Creation of Social Science Data
SOCR8204 Causal Inference
A maximum of 6 units from completion of the following courses:
ANIP6503 Australian National Internships Program A
CBEA6070 ANU College of Business and Economics Internship Program (PG)
Study Options
| Year 1 48 units | COMP6730 Programming for Scientists 6 units | COMP6240 Relational Databases 6 units | STAT7055 Introductory Statistics for Business and Finance 6 units | SOCR8202 Using Data for Monitoring and Evaluation 6 units |
| COMP8430 Data Wrangling 6 units | STAT7038 Regression Modelling 6 units | SOCR8201 Asking the Right Questions: Designing Effective Data Collection 6 units | STAT6026 Graphical Data Analysis 6 units | |
| Year 2 | COMP8410 Data Mining 6 units | STAT8130 Generalised Linear Modelling 6 units | Stage 3 Elective Course 6 Units | Stage 3 Elective Course 6 units |
Admission Requirements
Applicants must present one of the following:
- A Bachelor degree or international equivalent with a minimum GPA of 5.0/7.0; or
- An ANU Graduate Certificate of Applied Data Analytics with a minimum GPA of 4.5/7.0; or
- A minimum of 10 years full-time equivalent work experience at OSCA Skill Level 1 in a field related to the program.
The GPA for a Bachelor program will be calculated from (i) a completed Bachelor degree using all grades and/or (ii) a completed Bachelor degree using all grades other than those from the last semester (or equivalent study period) of the Bachelor degree. The higher of the two calculations will be used as the basis for admission.
Ranking and English Language Proficiency: At a minimum, all applicants must meet program-specific academic/non-academic requirements, and English language requirements. Admission to most ANU programs is on a competitive basis. Therefore, meeting all admission requirements does not automatically guarantee entry.
In line with the University's admissions policy and strategic plan, an assessment for admission may include competitively ranking applicants on the basis of specific academic achievement, English language proficiency and diversity factors. Applicants will first be ranked on a GPA ('GPA1') that is calculated using all but the last semester (or equivalent) of the Bachelor degree used for admission purposes. If required, ranking may further be confirmed on the basis of:
- a GPA ('GPA2') calculated on the penultimate and antepenultimate semesters (or equivalent) of the Bachelor degree used for admission purposes; and/or
- demonstrating higher-level English language proficiency
Prior to enrolment in this ANU program, all students who gain entry will have their Bachelor degree reassessed, to confirm minimum requirements were met.
Further information: English language admission requirements and post-admission support
Diversity factors: As Australia’s national university, ANU is a global representative of Australian research and education. ANU endeavours to recruit and maintain a diverse and deliberate student cohort representative not only of Australia, but the world. In order to achieve these outcomes, competitive ranking of applicants may be adjusted to ensure access to ANU is a reality for brilliant students from countries across the globe.
Assessment of qualifications: Unless otherwise indicated, ANU will accept all Australian Qualifications Framework (AQF) qualifications or international equivalents that meet or exceed the published admission requirements of our programs, provided all other admission requirements are also met.
Where an applicant has more than one completed tertiary qualification, ANU will base the assessment on the qualification that best meets the admission requirements for the program. Find out more about the Australian Qualifications Framework: www.aqf.edu.au.
Unless otherwise indicated, where an applicant has more than one completed tertiary qualification, ANU will calculate the GPA for each qualification separately. ANU will base assessment on the best GPA of all completed tertiary qualifications of the same level or higher.
ANU uses a 7-point Grade Point Average (GPA) scale. All qualifications submitted for admission at ANU will be converted to this common scale, which will determine if an applicant meets our published admission requirements. Find out more about how a 7-point GPA is calculated for Australian universities: www.uac.edu.au/future-applicants/admission-criteria/tertiary-qualifications.
Pathways
CADAN
Indicative fees
Domestic Tuition Fees (DTF)
For more information see: http://www.anu.edu.au/students/program-administration/costs-fees
- Annual indicative fee for international students
- $57,640.00
For further information on International Tuition Fees see: https://www.anu.edu.au/students/program-administration/fees-payments/international-tuition-fees
Fee Information
All students are required to pay the Services and amenities fee (SA Fee)
The annual indicative fee provides an estimate of the program tuition fees for international students and domestic students (where applicable). The annual indicative fee for a program is based on the standard full-time enrolment load of 48 units per year (unless the program duration is less than 48 units). Fees for courses vary by discipline meaning that the fees for a program can vary depending on the courses selected. Course fees are reviewed on an annual basis and typically will increase from year to year. The tuition fees payable are dependent on the year of commencement and the courses selected and are subject to increase during the period of study.
For further information on Fees and Payment please see: https://www.anu.edu.au/students/program-administration/fees-payments
Scholarships
ANU offers a wide range of scholarships to students to assist with the cost of their studies.
Eligibility to apply for ANU scholarships varies depending on the specifics of the scholarship and can be categorised by the type of student you are. Specific scholarship application process information is included in the relevant scholarship listing.
For further information see the Scholarships website.
The Master of Applied Data Analytics is a 1.5 year full-time (or equivalent part-time) degree that provides students with:
- Exposure to contemporary methods and best practice in data analytics, data management, and evidence-based decision-making.
- Advanced training in statistics, computing, and applied research methods through courses designed for aspiring data analytics professionals.
- The opportunity to develop expertise in areas such as statistical modelling, machine learning, business analytics, social research, data collection, and program evaluation.
- Access to real-world datasets, including resources available through the Australian Data Archive, enabling students to apply analytical techniques to practical problems.
- Flexible study options that allow students to tailor their degree to their interests and career goals through a broad range of elective courses.
- Opportunities to undertake internships and other applied learning experiences that strengthen professional skills and industry engagement.
The program is taught on campus.
Career Options
ANU ranks among the world's very finest universities. Our nearly 100,000 alumni include political, business, government, and academic leaders around the world.
We have graduated remarkable people from every part of our continent, our region and all walks of life.
This program is available for applications to commence from first semester, 2027
Employment Opportunities
Graduates of the Master of Applied Data Analytics are well positioned for careers across government, business, consulting, research, and not-for-profit organisations. The program develops capabilities in data management, statistical modelling, machine learning, business analytics, research design, program evaluation, and evidence-based decision-making, preparing students for roles such as data analyst, business analyst, analytics consultant, policy analyst, research analyst, monitoring and evaluation specialist, and data scientist. The inclusion of applied coursework in statistics, computing, social research methods, and business analytics, together with opportunities for internships and engagement with real-world datasets, provides strong preparation for data-driven roles across a wide range of industries. Graduates may find employment with government agencies, consulting firms, technology companies, financial institutions, research organisations, international development agencies, and non-government organisations, both within Australia and internationally.
Learning Outcomes
- Select, adapt, apply, and communicate advanced data analytics methods and techniques.
- Apply data analytics to decision making about policy, business and service delivery.
- Examine current issues in data analytics using leading-edge research and practices in the field.
- Demonstrate strong cognitive, technical, and communication skills to collect, process, interpret and communicate the outcomes of data analytics problems.
- Communicate complex data analytics outcomes to diverse audiences.
Inherent Requirements
There are no inherent requirements for this program.
Further Information
Information on applying for exemptions from prior study can be found under the “First Year Advice” tab.
