Postgraduate programs in Applied Data Analytics


ANU offers postgraduate study opportunities for professionals interested in developing skills – or upskilling – in the area of data analytics.

These programs are designed to address a global shortage of graduates with skills in data analytics, which is vital to the development of high-quality, data-informed decision-making. They have wide-ranging applications for the Australian government, Australian businesses and the broader community, all of which are facing the challenge of how to use public data effectively and informatively.

The rapid expansion of the digital environment has increased the opportunity for data-driven innovation, but also the dangers of it. Being able to understand and anticipate developments in the manipulation and use of data will result in a workforce with a diverse skillset that ranges over computational, statistical and methodological approaches. These areas of expertise can be applied in a range of professional settings, from public health to national security, from education to consumer industry.

The data analytics programs focus on equipping students to apply their skills in solving problems that reflect ‘real’ conditions, as well as giving students familiarity with the underlying principles of ‘big data’ software systems. Real-world case studies are embedded in several key courses spread throughout the curriculum. Students undertaking the data analytics program should expect:

  • Exposure to best-practice in data analytics.
  • Cutting-edge courses in areas of relevance to data analysts.
  • Opportunities to develop detailed knowledge of one of three academic specialisations – computation, statistics, or social science.
  • Professional development for students already working in the data analytics field.
  • To pursue research of professional relevance.
  • Pathways and exit points which reflect students’ differing educational requirements, as well as varying degrees of technical proficiency and real-world expertise.

Programs of study

The Applied Data Analytics programs are designed to develop interdisciplinary knowledge across three foundational academic areas: computing, statistics and social science. Students will develop introductory knowledge of all three areas to learn how data analytics and data science can provide the evidence base to improve social and business outcomes. They will also develop a specialisation in one of these three areas.

There are three different program options, with the Graduate Diploma providing skills and practice to further develop core skills, and the masters giving students the opportunity to develop deep specialisation.

The program is designed to have flexible entry and exit points, reflecting the diverse student cohort with different professional backgrounds and varying levels of technical expertise. For example, a student enrolled in the Graduate Diploma can subsequently transfer to the Masters award, with credit for courses already completed. Equally, a student enrolled in the Masters who decides not to complete the full award program can request to exit with a Graduate Diploma, which requires fewer courses. The Graduate Certificate is available as an entry qualification for domestic students studying part-time online only.

Note for international students: international students are able to enrol in the Master of Applied Data Analytics. However, there are required to enrol in semester-long in person delivery mode of the Data Analytics courses, in compliance with student visa regulations.

Students who may wish to focus on data engineering should also consider, Graduate Certificate in Data Engineering.

I'm interested! Now what?

The application and enrolment process has 5 key stages:

Step 1: apply

Ready to apply? Head to the relevant Programs and Courses page for the program you're interested in. Follow the black "Apply" button to see the available options for domestic and international students.

For domestic applicants, you can find the application closing dates via the ‘course search’ function on the UAC website. See: UAC postgraduate applied data analytics

For international students, there are a number of rounds where you can apply for our main intakes. See: ANU international applications

Step 2: offer

Eligible applicants will receive an offer of admission by email from the ANU Admissions team. Sometimes the offer will be conditional, requiring you to provide additional documents or information. 

Step 3: accept

Follow the instructions contained in your offer letter to accept your place at the ANU. After completing the online acceptance process, you will receive an ANU logon and enrolment instructions from the Data Analytics team.

Step 4: enrol

You can then log on to ISIS, the ANU Interactive Student Information System, to enrol in your chosen courses.

Step 5: study

Online course material will be available to all enrolled students through the ANU Wattle portal. Wattle uses the same ANU ID number and password as ISIS and other ANU systems. Course material will become visible about a week before it commences.


Application process

Head to the relevant Programs and Courses page for the program you're interested in. Follow the black "Apply" button to see the available options for domestic and international students. Apply now for the:

  • Master of Applied Data Analytics
  • Graduate Diploma of Applied Data Analytics
  • or the Graduate Certificate of Applied Data Analytics.

For domestic applicants, you can find the application closing dates via the ‘course search’ function on the UAC website. See: UAC postgraduate applied data analytics

For international students, there are a number of rounds where you can apply for our main intakes. See: ANU international applications.

Delivery mode

For brief information on the delivery mode for any of the Applied Data Analytics Postgraduate programs please visit the program on Programs & Courses: Graduate Certificate in Applied Data Analytics, Graduate Diploma of Applied Data Analytics and the Master of applied Data Analytics.

International students should note that they are required to enrol in the semester-long oncampus versions of the Data Analytics courses.


Applicants who have completed a degree in a discipline related to Data Analytics may be eligible to receive credit towards their degree.

The ANU credit policy for coursework students states that credit cannot be given for study which predates the course for which credit is being sought by more than 7 years. See the Coursework Award Rules 2016’, section 3.3.1.

Students whose studies fall outside this 7-year window may be granted an exemption instead of credit. For example, a student whose database studies were completed in 2006 may be granted an exemption for COMP7240. In this case, the student’s degree is not shortened, but they can choose a different course with which to replace COMP7240.

In order to be formally assessed for academic credit, students must supply colour scans of original academic transcripts and course outlines for all relevant courses to The discipline conveners (COMP, STAT, SOCR) may also require students to supply a written statement against the learning outcomes for the ANU courses to justify why the student should receive credit.

More information:

Course schedule

**Note: These tables show only the intensive (i.e. online) iterations of these courses. For details of semester-long, on-campus versions of the same courses, please follow the course links available in the 'program structure' tab immediately above.

Application deadlines for each of these academic sessions are available through the ‘course search’ function on the UAC website. The below table is an indicative course schedule. For confirmation of course dates, please visit the relevant page on Programs and Courses – by searching for the Course code.

2022 intensive-mode courses


Course dates

Intensive week

Last date to enrol

Census date

Academic session

STAT7030 – Generalised Linear Models

Tao Zou

10 January - 11 March

 7-11 February

 21 January

 21 January


SOCR8204 – Advanced Social Science Approaches to Inform Policy Development and Service Delivery

Nicholas Biddle

COMP8430 – Data Wrangling

Peter Christen

10 January

COMP7240 – Introductory Databases

Qing Wang

 14 March - 13 May

  11-14 April


 14 March


 1 April


 Autumn 1

COMP8420 – Neural Networks, Deep Learning and Bioinspired Computing

Sabrina Caldwell

STAT7026 – Graphical Data Analysis

Priya Dev

 1 April

STAT6038 – Regression Modelling

 Francis Hui

 30 May - 29 July

 28 June - 4 July

 10 June

 10 June 

 Autumn 2

SOCR8202 – Using Data to Answer Policy Questions

 Matthew Gray

COMP6490 – Document Analysis

 Alex Matthews

 30 May

COMP7230 – Programming for Data Scientists

Dr Sergio Rodriguez Mendez

 8 August - 7 October

 5 - 9 September

 8 August

 19 August


COMP8410 – Data Mining

Kerry Taylor

SOCR8203 – Advanced Techniques in the Creation of Social Science Data


 19 August

STAT7055 – Introductory Stats for Business and Finance

Priya Dev

 3 October - 2 December

 31 October - 4 November

 21 October

 21 October


SOCR8201 – Introduction to Social Science

Nicholas Biddle


Enrolment patterns

You can download a recommended enrolment pattern for your individual situation: domestic or international.

Note that these patterns are strictly advisory. They are designed to help students navigate the degree by taking account of factors such as pre-requisites (what order you need to take some courses in) and scheduling constraints (some courses occur more frequently than others). You are free to vary these patterns, but the College cannot guarantee that a student who diverges from the recommended pattern will be able to complete the program in the minimum time.

Enrolment patterns for the Master of Applied Data Analytics:

Enrolment patterns for the Graduate Diploma of Applied Data Analytics:

Program structure

Check the 'Study' tab of the relevant Programs and Courses page to see each program requirements. 

In general, the Master program includes three stages.

Stage 1: Foundational courses

Stage 1 comprises four courses which are designed to introduce students to the key concepts of the Data Analytics program. The courses cover two technical disciplines – Statistics and Computer Science – and act as a re-skilling opportunity for students with some experience in these areas. Students coming from a technical background are highly likely to be granted recognition of prior learning for some or all of Stage 1. Students may choose to leave the program at the end of Stage 1 with a Graduate Certificate of Applied Data Analytics.

C1 - Introduction to Programming for Data Scientists (COMP7230)

C2 - Introduction to Database Concepts (COMP7240)

STAT1 - Introductory Statistics for Business and Finance (STAT7055)

STAT2 - Regression Modelling (STAT6038)

Stage 2: Core material

Stage 2 builds on the foundational courses in Stage 1, developing students’ knowledge across the program’s three main areas of Statistics, Computer Science and Social Science. In Stage 2, students will be given regular opportunities to apply their skills in solving problems that reflect real-world conditions. Students will also participate in teamwork as part of this integrated approach to learning. Students with extensive experience in one of the three disciplines may be granted recognition of prior learning for some of the courses in Stage 2, at the discretion of the program convener. Students may choose to leave the program with a Graduate Diploma of Applied Data Analytics after completing four courses from Stage 2 – eight courses in total, combined with those from Stage 1.

C3 - Data Mining (COMP8410)

C4 - Data Wrangling (COMP8430)

SS1 - Introduction to social science methods and types of data (SOCR8201)

SS2 - Using data to answer policy questions and evaluate policy (SOCR8202)

STAT3 - Generalised Linear Models (STAT7030)

STAT4 - Graphical Data Analysis (STAT7026)

Stage 3: Specialisation

Stage 3 continues to offer students the opportunity to upskill, by facilitating specialisation in one of the program’s three disciplines: Statistics, Computer Science, or Social Science. Students completing Stage 3 will take a further two courses after Stage 2, enabling them to apply their broad-based skills while refining their expertise in their chosen area. Students who complete this stage of the program will be awarded a Master of Applied Data Analytics.

C5 & C6 – Two courses from a choice of:

Statistical Machine Learning (COMP8600)

Document Analysis (COMP6490)

Bio-inspired Computing: Applications and Interfaces (COMP8420)

SS3 & SS4 – Two courses from a choice of:

Advanced techniques in the creation of social science data (SOCR8203)

Advanced social science approaches to inform policy development and service delivery (SOCR8204)

Online Research Methods (SOCR8006)

Social Research Practice (DEMO8082)

STAT5 & STAT6 – Two courses from a choice of:

Statistical Learning (STAT7040)

Introduction to Bayesian Data Analysis (STAT7016)

Principles of Mathematical Statistics (STAT6039)

Applied Time Series Analysis (STAT8002)

Frequently asked questions


What makes the Applied Data Analytics program different to other ANU Masters programs?

The Applied Data Analytics programs at ANU differs from other similar programs in that it offers both a broad-ranging curriculum and an opportunity to develop specialised skills in one particular area. Students enrolling in the Graduate Diploma or Masters are required to complete courses across three different academic disciplines – computer science, social science and statistics. Students cannot complete the program without attaining a certain level of proficiency in all three areas, resulting in graduates with an integrated and well-rounded understanding of cutting-edge data analytics. Masters students are also able to specialise in a discipline of their choosing, taking higher-level courses to give them the expertise they need in their professional fields. The ANU program focuses on real-world applications of data analytics techniques and toolsets, equipping graduates with the academic background to tackle practical problems.

What are the admission requirements for the Graduate Diploma and Masters programs?

Check the 'Admission & Fees' tab of the relevant Programs and Courses page to see the admission requirements for both domestic and international students. 

International students are eligible for admission with the equivalent of an Australian Bachelor or Honours degree – subject to the linked GPA requirements – but will be required to submit a CV to demonstrate relevant work experience for admission to the Masters.

All applicants will also need to provide evidence of meeting ANU English language requirements. For international students, this can commonly be met with an up-to-date copy of an approved English language test (e.g. TOEFL, IELTS).

Am I admissible if I don’t have a Bachelor degree?

Domestic applicants who do not have a Bachelor degree may be eligible for admission to the program on the basis of professional equivalency. This means that the applicant has been assessed by the relevant delegated authorities as meeting the academic entry requirements without completing formal university study.

Applicants wishing to discuss whether they are eligible for admission without a degree should consult the program convener, Associate Professor Kerry Taylor (

Is the program open to international students?

The Master of Applied Data Analytics is available to international students. Owing to student visa restrictions, international students are required to study in the traditional on-campus semester mode, and to maintain a full-time study load of four courses per semester.

International students should be aware that the Data Analytics program has a work experience component as part of the admission requirements. This may mean that some international students are not eligible for admission, but students should check with to be sure.

Finally, international students should note that the Data Analytics program is a 72-unit Masters, which takes 1.5 years to complete in full-time mode. Therefore, this program does not meet the eligibility requirement for students to apply for permanent residency. Students should consult the Department of Home Affairs for further information.

What is the ANU English language policy, and to whom does it apply?

The ANU English language requirements for admission policy applies to all students of the ANU, whether domestic or international.

All applicants to the ANU must meet these requirements requirements, based on citizenship status, prior study, and English language tests.

What is the difference between ‘award’ and ‘non-award’ programs?

Both the Graduate Diploma and the Masters are ‘award’ programs. This means that they are programs of study which enable the student to graduate with a formal academic award, once all requirements are met.

The non-award program enables students to enrol in any course which interests them and for which they meet the pre-requisites. The completion of non-award courses does not enable students to graduate with a Graduate Diploma or a Masters, regardless of how many courses they complete. However, students who have completed non-award courses which are part of the Applied Data Analytics program are able to request academic credit for these courses, should they subsequently enrol in the Graduate Diploma or Masters programs.

The ANU is not currently accepting non-award applications for the Data Analytics program. If you have an enquiry about non-award study, contact

What documents do I need to include with my application?

You will need to include colour scans of original academic transcripts, and of any change-of-name documentation (e.g. marriage certificate). Please note that greyscale scans of academic transcripts are not acceptable, nor are colour photographs of original transcripts.

You should also iclude a copy of your curriculum vitae (CV) if you are seeking admission based on a combination of your qualifications and work experience.

All applicants will also need to provide evidence of meeting ANU English language requirements. For international students, this can commonly be met with an up-to-date copy of an approved English language test (e.g. TOEFL, IELTS).

How do I know if my application has been successful?

You will receive an email from the ANU Admissions team, to the email address nominated on your application. Depending on the information you provided, you may receive either a full offer for study or a conditional offer for study. Conditional offers for study require you to meet certain conditions before you can accept the offer.


Teaching and assessment

Why does the Applied Data Analytics program teach outside normal university semesters?

The Applied Data Analytics program was designed to be taught in online intensive mode for working professionals. Normal university semesters are not generally suited for this teaching format. Instead of being constrained by fixed dates for Semesters 1 and 2, the Data Analytics program teaches courses staggered throughout the year in the non-standard ANU teaching sessions – Autumn, Winter, Spring etc. This model is also used by other areas in the ANU that teach specialised professionally-focused courses, including the College of Law and the Crawford School of Public Policy.

The courses included in the Data Analytics program are also available in on-campus semester-long mode for international students, and for students enrolled in other ANU programs. For example, COMP8410 (Data Mining) is a compulsory course under the Master Applied Data Analytics and an elective/specialisation course under the Master of Computing.

What is an ‘academic session’?

An academic session is the specific period of the academic year to which a course belongs. The Data Analytics program teaches in both standard and non-standard academic sessions. Non-standard academic sessions are seasonal:

  • Summer – January to March
  • Autumn – April to June
  • Winter – July to September
  • Spring – October to December

Non-standard seasonal sessions run in parallel with Semesters 1 and 2. Semester 1 runs from January to June, at the same time as the Summer and Autumn sessions; Semester 2 runs from July to December, at the same time as the Winter and Spring sessions.

Students need to know in which academic session their course is being taught, because this is how you make sure you’re enrolling in the right course in your ISIS account. Once you’ve successfully added a course to your enrolment, the course will display on the ISIS home screen under the relevant academic session.

How do online intensive courses work?

Online intensive courses in the Applied Data Analytics program are run over nine weeks. The first four weeks comprise online learning and assessment through the ANU Wattle portal. The fifth week is spent full-time on campus at the ANU. The final four weeks are a further period of online teaching and assessment. We call this mode 4+1+4. Therefore, eight weeks of each course may be completed online from anywhere, and one week must be spent on campus in Canberra.

Can I take two online intensive courses that are running simultaneously?

Students cannot take two intensive courses with same start and finish dates. This is because they will have the same on-campus intensive week, and students can only attend one of these at a time. Where courses are offered concurrently (e.g. Spring – STAT7055 / SOCR8202), students will be required to choose one or the other.

Can students complete the program in full-time mode?

At present, it is not possible for students to undertake the online intensive program in full-time mode. The maximum number of online intensive courses available is five per annum – this is slightly more than a 50 per cent study load.

Students who would like to enrol in a mixture of online courses and traditional on-campus semester-long courses are able to complete the program in full-time mode. For advice about how to mix on-campus and online courses, please contact Please note that mixing on-campus and online courses is only available to domestic students; international students are required to study on campus and to maintain a full-time study load.

Is the on-campus intensive week compulsory?

Yes, the on-campus intensive week is compulsory for all students. Exceptions will be made only in the case of serious and unforeseen circumstances (e.g. sudden illness, accident or bereavement). Otherwise, all students are expected to participate in all aspects of the on-campus intensive week, and students will not be given exemption on the grounds of professional workload. The intensives are a crucial part of learning development and cohort-building for all courses, and students should fully consider this expectation when choosing to undertake the program.

How do I know what the pre-requisites are for any particular course?

Pre-requisites and any assumed knowledge are detailed on the Programs and Courses entry for each course. Below is a table of the pre-requisites for the courses included in the Applied Data Analytics program.

Please note that these pre-requisites only apply to students enrolled in the Applied Data Analytics program. Students enrolled in other programs may be subject to other pre-requisites, as detailed on Programs and Courses.




Required prior courses

Stage One

STAT7055 Intro Stats for Business


STAT7001 Applied Statistics


COMP7230 Programming for Data Scientists


COMP7240 Introductory Databases


Stage Two

SOCR8201 Introductory Social Science


SOCR8202 Using Data to Answer Policy Questions


STAT6039 Mathematical Statistics

STAT7055 or STAT7001

STAT7026 Graphical Data Analysis


COMP8410 Data Mining

COMP7230 and COMP7240

COMP8430 Data Wrangling

COMP7230 and COMP7240

Stage Three

SOCR8203 Advanced Social Science Techniques

SOCR8201 or SOCR8202

SOCR8204 Policy Development and Service Delivery

SOCR8201 or SOCR8202

SOCR8006 Online Research Methods

SOCR8201 or SOCR8202

SOCR/DEMO8082 Social Research Practice

SOCR8201 or SOCR8202

STAT7016 Bayesian Data Analysis

STAT7001 and STAT6039

STAT7030 Linear Models


STAT7040 Statistical Learning

STAT7001 and STAT6039

STAT8002 Applied Time Series Analysis

STAT7001 and STAT6039

COMP6490 Document Analysis

COMP7230 and COMP7240 and COMP8410 and STAT6039

COMP8420 Bio-Inspired Computing

COMP7230 and COMP7240, plus either COMP8410 or COMP8430

COMP8600 Machine Learning

COMP7230 and COMP7240 and COMP8410 and STAT6039

What is the assessment structure for each course?

The assessment structure varies from course to course, depending on the individual convener and the material being taught. However, all ANU courses include multiple forms of assessment, both formative (identifying areas of academic strength and weakness) and summative (finding out how well you’ve achieved the learning outcomes of the course). You can expect to be assessed in different ways throughout the course, not just at the end. Many courses will include some form of group assessment, reflecting the real-world concerns of the program, because large-scale data analysis is often performed in a team environment.

How do I find out if a particular course is suitable for my skillset?

We recommend you view the relevant Programs and Courses entry for the course in question. These will provide a summary of the course material, and of the learning outcomes for the course. You may also consult the convener for the relevant course, who will be able to answer specific questions and to provide you with a course outline.



How much will my degree cost?

For comprehensive information on other fees, funding, and payments, visit Fees and payments

Academic tuition fees are charged on an individual course basis. Students will receive an invoice for each semester or session they enrol in. Indicative annual program tuition fees are published on Programs and Courses (see the 'Admissions and Fees' tab). You can also see the latest individual course fees on the relevant Programs and Course course page (see the 'Fees' tab). does not include the cost of any textbooks (which not all courses will require), or the cost of travelling to and attending the on-campus intensive component.

What scholarships are available?

The College has a small number of scholarships available to postgraduate students, including a 25 per cent fee reduction for domestic coursework students. Some scholarships will require an application, while others will be available for automatic consideration.

More information: Find a scholarship

Are there any Commonwealth Supported Places (CSPs) for this program and how do I apply?

Postgraduate Commonwealth Supported Place (CSP) are limited in number, based on academic merit, and highly competitive. There is no application process for a CSP as domestic students who have received an offer of admission to a CSP-eligible postgraduate program are automatically considered prior to commencement each semester. 

More information: Postgraduate commonwealth supported places

Is this program eligible for a FEE-Help loan?

Australian citizens enrolled in this program are eligible to defer their tuition fees through a FEE-Help loan. New Zealand citizens and Australian permanent residents can access FEE-Help in certain specific situations, outlined on the Study Assist website.

International students are not able to access FEE-Help, and will be required to pay tuition in full at the start of each semester.

What is the ‘census date’ for each course?

The census date for a course is the date at which students are regarded as liable for their tuition fees, regardless of whether they complete the academic requirements of the course. Up to census date, students can ‘drop’ a course online through ISIS without incurring any financial penalty. Students dropping a course after census date will remain liable for the tuition. The only exception to this is students who are approved for late withdrawal from a course. Late withdrawals apply to students who encounter sudden and unexpected circumstances which prevent them from completing the course (e.g. serious illness, accident or bereavement).

The census date for a course is determined by its start date. The census date occurs roughly a third of the way through the course. 

For courses taught in typical semester-long on-campus mode, census dates remain the same every year: 31 March for Semester 1 courses, and 31 August for Semester 2 courses. More information: see University calendar

How can I organise for my employer to pay my tuition fees?

Students whose employers wish to pay their tuition invoices need to set up a tuition sponsorship through the ANU Student Finance team. Sponsored students will not receive a tuition invoice through their ISIS accounts – the invoice goes straight from ANU Student Finance to the nominated contact at the sponsoring organisation. Students who have a tuition sponsorship will not be charged late fees if their sponsor does not pay by the due date on the invoice – the ANU Student Finance team negotiates directly with the sponsor for payment.

Students who choose to download their invoices from ISIS and to provide these to their employers for payment should note that the student will be charged late fees if payment does not arrive by the due date. This is because the above arrangement does not constitute a tuition sponsorship, even if the student has provided the invoice to their employer. From the ANU point of view, students are considered to be self-funded unless they have an official ANU tuition sponsorship in place.

Students who do not wish to set up a tuition sponsorship are recommended to pay their own tuition by BPay or credit card through their ISIS account, and then to seek reimbursement from their employer. This arrangement minimises the chance that students will be left with additional fees if an employer does not pay the invoice on time.

How do I view and pay my tuition fee invoice?

From the home screen in ISIS, students should select ‘check your invoice’ to see their most recent outstanding invoice. Students wishing to consult previous invoices should click ‘invoice history’ for a full list.

Am I Centrelink-eligible while studying in the Applied Data Analytics program?

The Applied Data Analytics program is not considered an approved coursework Masters program for the purposes of student-support payments from Centrelink. However, students who believe they qualify for Austudy or for Youth Allowance (Student) should contact the Department of Human Services directly for clarification.

General questions

Do I need a student card if I am a domestic intensive student?

Students who do not reside in the ACT and who do not intend to use ANU infrastructure during their degree may not need a student card. However, we recommend that all students acquire a student card just in case. You can arrange this in person during one of your on-campus intensive weeks. Student cards are available over the counter with approved photo identification (e.g. passport, driver’s licence) from the ANU Student Central.

Please note that students must have accepted their offers for study and be enrolled in a course before they are eligible to hold a student card. Interstate students can request that a student card be mailed to them, subject to certain restrictions.

Students who reside in the ACT and wish to use ANU library or computer laboratory facilities will need a student card to access the relevant buildings.

What are the arrangements for the on-campus intensive week for each course?

Arrangements for the on-campus intensive week vary from course to course, but students should expect to be on campus every day (Monday to Friday) from 0900 to 1700. Details of the building locations and timetables for the intensive weeks will be emailed to all enrolled students one week in advance, along with maps of the ANU campus and other information to assist those new to Canberra and to the ANU.

Can I get recognition of prior learning (RPL) for some of my previous university study?

You may be eligible for recognition of prior learning (RPL) if you have completed related studies in a previous university degree. At the ANU, RPL is called academic status and takes two forms – credit and exemption.

As described in the above tab labelled ‘credit’, students who are awarded credit will have their total academic program shortened by the number of course for which they are granted credit. In other words, they are regarded as having completed the courses in question.

Students who are granted exemption do not have to take the course for which they have been granted exemption, and are permitted to replace the exempted course with another course of their choosing, from an approved list of program enclosures. A student who receives exemption does not have their program shortened.

For more information about the restrictions on the awarding of academic status, please see section 3.1 of the Coursework Awards Rule:

Some examples of credit and exemption scenarios:

  • Student A has worked in the Australian Public Service for 15 years but has no formal qualifications. He has had significant experience in programming and is able to demonstrate this. On the basis of his work experience, he is admitted to the Master of Applied Data Analytics. He does not receive any credit, so the duration of his program remains the same. Due to his experience in programming, he is able to get an exemption for COMP7230, a compulsory course, which he chooses to replace with another course under the ‘Data Science’ category.
  • Student B has worked in the Australian Public Service for 5 years and has completed a Bachelor of Economics within the last 10 years. After submitting a credit application – including his transcript and course outlines – he is granted credit for STAT7055. He is not required to replace this course with another and so his program is shortened by one course.
  • Student C applies to study three courses included in the Master of Applied Data Analytics as a non-award student. She has completed a Master of Computing within the last 10 years. She is not able to receive credit as she is studying as a non-award student. However, as she is considering applying for the Master of Data Analytics later, she seeks advice regarding the credit she would be eligible for. She is told that she would receive credit for COMP7230 and COMP7240 and so does not have to complete these courses. When she transfers into the Masters program, the duration of her course will be shortened by two courses, plus whatever courses she has undertaken as a non-award student.

Does the ANU consider MOOCs for admission and/or recognition of prior learning?

If the MOOC for which the student is seeking credit is determined to be equivalent in learning and assessment to a 6-unit ANU course, then the ANU may choose to grant credit, at the discretion of the program convener. For a MOOC to be credit-eligible, it must be taught by a reputable university, as defined by the Australian government Department of Education and Training’s policy on the recognition of overseas qualifications.

Can I appeal a decision about academic credit?

If you are unhappy with the decision regarding your application for academic status, you can appeal to the Associate Dean (Education) for the relevant College. The Data Analytics program teaches across three ANU Colleges – Business and Economics, Engineering and Computer Science, and Arts and Social Sciences – and each College has its own AD(E).

Applications to appeal a credit decision must be submitted in writing to, and the Data Analytics team will identify the correct College for the resolution of your appeal.


Information for members of the Australian Public Service (APS)

Do I need departmental support/endorsement to enrol in this program?

You do not need departmental support to enrol in the Data Analytics program – if you meet the admission requirements, then you are eligible.

However, if you wish to access study leave or other flexible arrangements through your employer, then the ANU recommends consulting your professional development or learning support contacts before enrolling in the program.

If my department has encouraged me to apply for this program, and has coordinated my application process, does this mean my tuition is fully funded?

Students should not assume that their tuition is employer-funded unless they have specifically consulted their employer about tuition arrangements, and have received written assurance that the employer has entered into a tuition sponsorship with the ANU. The ANU will not solicit tuition sponsorships on behalf of students. It is the student’s responsibility to secure the employer’s financial support, at which point the Data Analytics team ( is happy to assist with the logistics of setting up the sponsorship.

Students should check their ISIS account regularly to see whether they have any invoices owing. Even if you are a sponsored student, it’s a good idea to keep an eye out for invoices, because an unexpected account is a sign that something may not be functioning correctly with your sponsorship.

Can APS students access FEE-Help?

APS students can access FEE-Help, provided that they are Australian citizens. Permanent residents and New Zealand citizens are able to access FEE-Help in certain limited situations.


Glossary of useful ANU terms

Award A qualification conferred by the University and certified by a testamur.
  • Award names and relevant specialisations appear on a graduate's testamur.
  • Different plans may lead to different awards though some lead to the same award.
Program In an academic sense , a program is a structured sequence of study - normally leading to the Award of one or more degrees, diplomas or certificates. In a system sense, a program is a grouping of one or more academic plans around a particular theme, Awards, or set of admission requirements.
Course A subject of scholarly study taught:
  • in a connected series of lectures or demonstrations
  • by means of practical work including the production by students of essays or theses or case studies, or the attendance and participation by students in seminars or workshops.
Each course requires a course outline.
A four character alphabetic subject area code and a four digit numeric catalogue number identify each course. The first digit denotes the state/year of the program in which the course is normally taken. Each course is normally assigned a unit value that is a measure of the proportion of the academic progress that a course represents within the total credit for the program
Unit This is an indicator of the value of the course within the total program. Most courses are valued at 6 units. Units are used to track progress towards completing a plan. Full -time students normally undertake 24 units of courses each semester.
Non - award study Study that does not lead to the award of a degree, diploma, or certificate, but consists of a course or work requirement that may be at undergraduate or graduate coursework level. [Note: non- award study does not include studies undertaken on a non- award basis within the meaning of HES Act.]
Credit The granting of credit is an evaluation process that assesses the individual's prior formal, non- formal, and informal learning to determine the extent to which the individual has achieved the required learning outcomes, competency outcomes, or standards for entry to, and/or partial or total completion of, a qualification.
Exemption Some students may be exempt from undertaking a compulsory c ourse for the program on the basis of previous completion of the course, or an equivalent course. However, a course of equivalent unit value must be substituted. An exempted course counts towards program requirements and satisfied pre- requisite requirement s for other courses but the unit value of the exempted course does not count towards the units taken towards the program.

Other terms can be found in the Student policies and procedures glossary

Updated:  10 August 2021/Responsible Officer:  Dean, CECS/Page Contact:  CECS Marketing