- Length 1 year full-time
- Minimum 48 Units
- Academic plan DADAN
- CRICOS code 097201M
- UAC code
Field of Education
- Mathematical Sciences NEC
The Graduate Diploma of Applied Data Analytics requires the completion of 48 units, which must consist of:
24 units from completion of the following compulsory courses:
COMP7230 Introduction to Programming for Data Scientists
COMP7240 Introduction to Database Concepts
STAT7055 Introductory Statistics for Business and Finance
STAT7001 Applied Statistics
24 units from completion of courses from the following list:
COMP8410 Data Mining
COMP8430 Data Wrangling
SOCR8201 Introduction to social science methods and types of data
SOCR8202 Using data to answer policy questions and evaluate policy
STAT6039 Introductory Mathematical Statistics
STAT7026 Graphical Data Analysis
STAT7040 Statistical Learning
A completed Bachelor degree with Honours or equivalent in any discipline from a recognised university
A completed Bachelor degree or international equivalent + 1 year of relevant work experience.
You must be one of the following:
- an Australian citizen
- an New Zealand citizen (or dual citizenship holders of either Australia or New Zealand)
- an Australian permanent resident
- an Australian humanitarian visa holder
Applicants who have completed a degree in a cognate discipline may be eligible to receive credit in line with the ANU Graduate Coursework Award Rules towards their Graduate Diploma of Applied Data Analytics degree
Actuarial Studies, Anthropology, Computer Science, Criminology, Demography/Population Studies, Engineering, Epidemiology/Public Health, Finance, Information Technology, Maths, Physics, Political Science, Psychology, Sociology, Statistics
- Annual indicative fee for domestic students
For more information see: http://www.anu.edu.au/students/program-administration/costs-fees
For further information on International Tuition Fees see: https://www.anu.edu.au/students/program-administration/fees-payments/international-tuition-fees
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 Graduate Diploma of Applied Data Analytics is a 1 year full-time (or equivalent part-time) degree that provides students with:
- Exposure to best practice in data analytics.
- Cutting edge courses in areas of relevance to data analytics practitioners.
- An opportunity to deepen knowledge in one of the three areas of computation, statistics, or social science.
- Professional development for practicing data analytics professionals.
- The opportunity to undertake research of professional relevance.
The program will be taught in intensive blended mode with students expected to be enrolled part-time.
Graduates from ANU have been rated as Australia's most employable graduates and among the most sought after by employers worldwide.
The latest Global Employability University Ranking, published by the Times Higher Education, rated ANU as Australia's top university for getting a job for the fourth year in a row.
Upon successful completion, students will have the skills and knowledge to:
- Apply computing, statistical, and social science principles to solve data analytics problems;
- Apply data analytics methods and techniques to decision making about policy, business and service delivery;
- Contribute as an effective member to the performance of a data analytics workplace;
- Demonstrate basic technical expertise in computing, statistics, and social science as relevant to data analytics.
- Be able to work to specification and according to a deadline, document tasks undertaken, and report outcomes to a third party.
- Be capable of independent learning with some ability to evaluate critically work undertake.
Students will need to install certain free software packages in order to successfully complete COMP7230. Please see the ‘Additional Information’ section on course information page.