At a minimum, all applicants must meet program-specific academic/non-academic requirements, and English language requirements. Admission to ANU programs is on a competitive basis. Therefore, meeting all admission requirements does not automatically guarantee entry.
A Bachelor degree with Honours or international equivalent with a minimum GPA of 5.0/7.0
Or a Bachelor degree or international equivalent with a minimum GPA of 5.0/7.0, plus at least 3 years of relevant work experience.
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.
Academic IELTS and IELTS Indicator: An overall score of 6.5 with a minimum of 6.0 in each component of the test.
TOEFL - internet based test : An overall score of 80, with a minimum of 20 in Reading and Writing and 18 in Speaking and Listening.
PTE Academic: An overall score of 64 with a minimum score of 55 in each of the communicative skills.
TOEFL - paper based test: A score of 570 with a TWE* score of 4.5.
Cambridge CAE Advanced (Post 2015): An overall score of 176 with a minimum of 169 in all sub-skills.
The Master of Applied Data Analytics is a 1.5 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.
CRICOS CODE: 097058B
More info: Click here
Program Requirements
The Master of Applied Data Analytics requires the completion of 72 units, which must consist of:
48 units from completion of the following compulsory courses:
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
STAT6038 Regression Modelling
STAT7030 Generalised Linear Models
STAT7026 Graphical Data Analysis
STAT7055 Introductory Statistics for Business and Finance
6 units from completion of courses from the following list:
COMP6240 Relational Databases
COMP7240 Introduction to Database Concepts
6 units from completion of courses from the following list:
COMP6730 Programming for Scientists
COMP7230 Introduction to Programming for Data Scientists
12 units from completion of courses from any of the following lists:
Computer Science
COMP6490 Document Analysis
COMP8420 Neural Networks, Deep Learning and Bio-inspired Computing
COMP8600 Statistical Machine Learning
Social Science
SOCR8082 Social Research Practice
SOCR8006 Online Research Methods
SOCR8203 Advanced Techniques in the Creation of Social Science Data
SOCR8204 Advanced Social Science Approaches to Inform Policy Development and Service Delivery
Statistical Data Analysis
STAT7016 Introduction to Bayesian Data Analysis
STAT6039 Principles of Mathematical Statistics
STAT7040 Statistical Learning
STAT8002 Applied Time Series Analysis
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.
OSHC: 609 $ per year
