English language requirements
Overall IELTS score of 6.5 with no band less than 6 (or equivalent). More information is available at www.ielts.org
One year part-time
The sheer volume and complexity of data already at the fingertips of businesses and research organisations gives rise to challenges that must be solved by tomorrow’s graduates. With an increasing emphasis on the use of data to inform day-to-day operations and long-term strategic decisions, modern organisations are reliant on data analysts. This course will equip you with the essential skills and knowledge in data analytics to meet this demand.
With a focus on fundamental data analytics, this course covers foundation skills, security and privacy issues, research and development, and real-world analytics. You will learn to use data to support organisational decision-making, ensuring you graduate ready for employment across a range of industries, or to undertake further studies in IT and data science.
This course is ideal for students without a computing background, as well as those who would like to support their industry experience with a recognised academic qualification.
- Award granted
- Graduate Certificate of Data Analytics
2022 course information
- Deakin code
- Postgraduate (Graduate Certificate and Graduate Diploma)
- Approval status
This course is approved by the University under the Higher Education Standards Framework.
- Australian Qualifications Framework (AQF) recognition
The award conferred upon completion is recognised in the Australian Qualifications Framework at Level 8.
To complete the Graduate Certificate of Data Analytics, students must attain 4 credit points (one year of part-time study), which must include the following:
- Three (3) credit points of core units
- One (1) credit point of level 7 SIT or MIS coded electives
- Completion of STP050 Academic Integrity (0-credit point compulsory unit)
Year 1 - Trimester 1
One (1) credit point of level 7 SIT or MIS coded electives
Campuses by intake
Campus availability varies per trimester. This means that a course offered in Trimester 1 may not be offered in the same location for Trimester 2 or 3. Read more to learn where this course will be offered throughout the year.
Trimester 1 - March
- Start date: March
- Available at:
- Cloud Campus
Trimester 2 - July
- Start date: July
- Available at:
- Cloud Campus
Trimester 3 - November
- Start date: November
- Available at:
- Cloud Campus
INTERNATIONAL STUDENTS – Please note that due to Australian Government regulations, student visas to enter Australia cannot be issued to students who enrol in Deakin’s Cloud Campus.
Mandatory student checks
Any unit which contains work integrated learning, a community placement or interaction with the community may require a police check, Working with Children Check or other check.
You can expect to participate in a range of teaching activities each week. This could include classes, seminars, practicals and online interaction. You can refer to the individual unit details in the course structure for more information. You will also need to study and complete assessment tasks in your own time.
Reasonable adjustments to participation and other course requirements will be made for students with a disability. Click here for more information.
Entry will be based on performance in:
- Bachelor degree in any discipline OR
- 2 years related work experience OR
- Evidence of academic capability judged to be equivalent
IELTS / English language requirements
Please note that English language requirements exist for entry to this course and you will be required to meet the English language level requirement that is applicable in the year of your commencement of studies.
It is the students’ responsibility to ensure that she/he has the required IELTS score to register with any external accredited courses. (more details)
Deakin University offers admission to postgraduate courses through a number of Admission categories. To be eligible for admission to this program, applicants must meet the course requirements.
All applicants must meet the minimum English language requirements.
Please note that meeting the minimum admission requirements does not guarantee selection, which is based on merit, likelihood of success and availability of places in the course.
For more information on the Admission Criteria and Selection (Higher Education Courses) Policy visit the Deakin Policy Library
Recognition of prior learning
Deakin aims to provide students with as much credit as possible for approved prior study or informal learning which exceeds the normal entrance requirements for the course and is within the constraints of the course regulations.
Students are required to complete a minimum of one-third of the course with Deakin, or four credit points, whichever is the greater. In the case of certificates, including graduate certificates, a minimum of two credit points within the course must be completed with Deakin.
You can also refer to the Recognition of Prior Learning Page which outlines the credit that may be granted towards a Deakin degree and how to apply for credit.
Recognition of Prior Learning may be granted to applicants based on prior studies and/or equivalent industry experience.
Fees and scholarships
The 'Estimated tuition fee' is provided as a guide only based on a typical enrolment of students completing this course within the same year in which they started. The cost will vary depending on the units you choose, your study load, the length of your course and any approved Recognition of Prior Learning you have.
The 'Estimated tuition fee' is calculated by adding together four credit points of study. Four credit points is used as it represents a typical enrolment load for a Graduate Certificate.
Each unit you enrol in has a credit point value. You can find the credit point value of each unit under the Unit Description by searching for the unit in the Handbook.
Learn more about tuition fees.
A Deakin scholarship could help you pay for your course fees, living costs and study materials. If you've got something special to offer Deakin - or maybe you just need a bit of extra support - we've got a scholarship opportunity for you. Search or browse through our scholarships
If you’re a Deakin alumnus commencing a postgraduate award course, you may be eligible to receive a 10% reduction per unit on your enrolment fees.
Applications can be made directly to the University through StudyLink Connect - Deakin University's International Student Application Service. For information on the application process and closing dates, see the How to apply web page.
Further study options:
Upon completion of the Graduate Certificate of Data Analytics, you could use the credit points you’ve earned to enter into further study, including:
S777 Master of Data Science
Deakin's Graduate Certificate of Data Analytics prepares students for professional employment across all sectors as data analytics specialists. Data analysts may find employment with organisations who make data-driven decisions, in areas including software development, pharmaceutical discovery, marketing, consulting, manufacturing,
financial services, telecoms, e-commerce, retail, health care, public services, information security and more.
Course learning outcomes
Deakin's graduate learning outcomes describe the knowledge and capabilities graduates can demonstrate at the completion of their course. These outcomes mean that regardless of the Deakin course you undertake, you can rest assured your degree will teach you the skills and professional attributes that employers value. They'll set you up to learn and work effectively in the future.
Deakin Graduate Learning Outcomes
Course Learning Outcomes
Discipline-specific knowledge and capabilities
Develop data analytics solutions based on user requirements by applying foundational knowledge of real world analytics concepts and technologies.
Communicate data analytical solutions as appropriate to the context to inform, motivate and effect change utilising a range of verbal, graphical and written methods, recognising the needs of diverse audiences.
Use digital media to locate and collect information to prepare for data analysis.
Use the frameworks of logical and analytical thinking to evaluate data analytics information and user requirements.
Design solutions for automating data analysis processes by applying foundational technical knowledge and tools.
Demonstrate the ability to work autonomously in order to meet requirements.
Engage in professional and ethical behaviour in the collection, processing, and presentation of data.
Approved by Faculty Board 27 June 2019