single degree

Master of Applied Data Analytics

A single 1.5 year graduate degree offered by the ANU College of Engineering and Computer Science

MADATAN
  • Length 1.5 year full-time
  • Minimum 72 Units
  • Field of Education
    • Mathematical Sciences not else
  • Length 1.5 year full-time
  • Minimum 72 Units
  • Field of Education
    • Mathematical Sciences not else

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.

Career Options

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.

Learning Outcomes

Upon successful completion, students will have the skills and knowledge to:

  1. Select, adapt, apply, and communicate advanced data analytics methods and techniques;
  2. Apply data analytics to decision making about policy, business and service delivery;
  3. Examine current issues in data analytics using leading-edge research and practices in the field;
  4. Demonstrate strong cognitive, technical, and communication skills to work independently and collaboratively to collect, process, interpret and communicate the outcomes of data analytics problems; and
  5. Communicate complex data analytics outcomes to diverse audiences.

Further Information

Please provide the following when you apply:

  • CV
  • Graduation certificates (testamurs) and academic transcripts for all formal study

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.

Admission Requirements

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. 

Applicants who have completed a degree in a cognate discipline from a recognised university may be eligible to receive coursework credit towards this degree, in line with the ANU Coursework Award Rules.

Cognate Disciplines

Actuarial Studies, Anthropology, Computer Science, Criminology, Demography/Population Studies, Engineering, Epidemiology/Public Health, Finance, Information Technology, Maths, Physics, Political Science, Psychology, Sociology, Statistics.

English Language Requirements

All applicants must meet the University’s English Language Admission Requirements for Students.

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 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

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

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.

Annual indicative fee for domestic students
$32,256.00

For more information see: http://www.anu.edu.au/students/program-administration/costs-fees

Annual indicative fee for international students
$43,200.00

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.

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:

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 Principles of Mathematical Statistics
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:

COMP1040 The Craft of Computing
COMP6730 Programming for Scientists
COMP7230 Introduction to Programming for Data Scientists

6 units from completion of courses from the following list:

STAT6038 Regression Modelling
STAT7001 Applied Statistics 

 

12 units from completion of courses from any of the following lists:

Computer Science
COMP6490 Document Analysis
COMP8420 Bio-inspired Computing: Applications and Interfaces
COMP8600 Introduction to 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 
STAT7030 Generalised Linear Models
STAT7040 Statistical Learning
STAT8002 Applied Time Series Analysis

Study Options

Year 1 48 units COMP1040/ COMP6730/ COMP7230 6 units COMP6240 Relational Databases 6 units OR COMP7240; STAT7055 Introductory Statistics for Business and Finance 6 units SOCR8202 Using Data to Answer Policy Questions and Evaluate Policy 6 units
COMP8410 Data Mining 6 units STAT6039 Principles of Mathematical Statistics 6 units SOCR8201 Introduction to Social Science Methods and Types of Data 6 units Stage 3 Elective Course 6 units
Year 2 COMP8430 Data Wrangling 6 units STAT7001 Applied Statistics 6 units STAT7026 Graphical Data Analysis 6 units Stage 3 Elective Course 6 units
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