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Graduate Certificate of Data Analytics

Postgraduate coursework

With a focus on fundamental data analytics and skills, delve into security and privacy issues, research and development and real-world analytics.

Key facts

Duration

0.5 year full-time or part-time equivalent

Key dates

Direct applications to Deakin for Trimester 3 2024 are closed.

Direct applications to Deakin for Trimester 1 2025 close 16 February 2025

Current Deakin Students

To access your official course details for the year you started your degree, please visit the handbook

Course overview

The sheer volume and complexity of data already at the fingertips of businesses and research organisations presents 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.

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Course information

Award granted
Graduate Certificate of Data Analytics
Year

2025 course information

Deakin code
S576
Level
Postgraduate (Graduate Certificate and Graduate Diploma)
Australian Qualifications Framework (AQF) recognition

The award conferred upon completion is recognised in the Australian Qualifications Framework at Level 8

Course structure

To complete the Graduate Certificate of Data Analytics, students must pass 4 credit points, which must include the following:

  • DAI001 Academic Integrity and Respect at Deakin (0-credit point compulsory unit)
  • 3 credit points of core units
  • 1 credit point of course electives

3

Core units

1

Course elective unit

4

Total

Core

  • Academic Integrity and Respect at Deakin (0 credit points)
  • Real World Analytics
  • Data Wrangling
  • Mathematics for Artificial Intelligence
  • Plus, 1 credit point from the following list of course electives:

  • Machine Learning
  • Statistical Data Analysis
  • Modern Data Science
  • Bayesian Learning and Graphical Models
  • Intakes by location

    The availability of a course varies across locations and intakes. This means that a course offered in Trimester 1 may not be offered in the same location for Trimester 2 or 3. Check each intake for up-to-date information on when and where you can commence your studies.

    Trimester 1* - March

    • Start date: March
    • Available at:
      • Burwood (Melbourne)
      • Online

      *Full time or part-time available

    Trimester 2* - July

    • Start date: July
    • Available at:
      • Burwood (Melbourne)
      • Online

      *Only part-time available

    Trimester 3* - November

    • Start date: November
    • Available at:
      • Burwood (Melbourne)
      • Online

      *Only part-time available

    INTERNATIONAL STUDENTS – Please note that due to Australian Government regulations, student visas to enter Australia cannot be issued to students who enrol in Deakin online.

    Course duration may be affected by delays in completing course requirements, such as failing of units or accessing or completing placements.

    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.

    Workload

    You can expect to participate in a range of teaching activities each week. This could include lectures, 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.

    Participation requirements

    Reasonable adjustments to participation and other course requirements will be made for students with a disability. More information available at Disability support services.

    Entry requirements

    Selection is based on a holistic consideration of your academic merit, work experience, likelihood of success, availability of places, participation requirements, regulatory requirements, and individual circumstances. You will need to meet the minimum academic and English language proficiency requirements to be considered for selection, but this does not guarantee admission.

    Academic requirements

    To be considered for admission to this degree you will need to meet at least one of the following criteria:

    • completion of a bachelor degree or higher in a related* discipline
    • completion of a bachelor degree or higher in any discipline and at least two years' relevant* work experience (or part-time equivalent).

    *Related to the broad field of Information Technology.

    English language proficiency requirements

    To meet the English language proficiency requirements of this course, you will need to demonstrate at least one of the following:

    Admissions information

    Learn more about Deakin courses and how we compare to other universities when it comes to the quality of our teaching and learning.

    Not sure if you can get into Deakin postgraduate study? Postgraduate study doesn’t have to be a balancing act; we provide flexible course entry and exit options based on your desired career outcomes and the time you are able to commit to your study.

    Recognition of prior learning

    The University 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 at Deakin University, 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 at Deakin.

    You can also refer to the recognition of prior learning (RPL) system which outlines the credit that may be granted towards a Deakin University degree and how to apply for credit.

    Fees and scholarships

    Fee information

    Estimated tuition fee - (CSP)?
    $4,013 - Commonwealth Supported Place (HECS)

    Learn more about fees.

    The available fee places for this course are detailed above. Not all courses at Deakin have Commonwealth supported places available.

    The 'Estimated tuition fee' is provided as a guide only and represents the typical tuition fees for students completing this course within the same year 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. The 'Estimated tuition fee' is calculated by adding together four credit points of a typical combination of units for your course.

    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 fees and available payment options.

    Scholarship options

    A Deakin scholarship might change your life. If you've got something special to offer Deakin – or you just need the financial help to get you here – we may have a scholarship opportunity for you.

    Search or browse through our scholarships

    Postgraduate bursary

    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.

    Learn more about the 10% Deakin alumni discount

    Apply now

    Apply directly to Deakin

    To apply, create an account in the Deakin Application Portal, enter your personal details and education experience, upload supporting documents and submit. Need help? Play this video, or contact one of our friendly future student advisers on 1800 693 888 or submit an online enquiry.

    Need more information on how to apply?

    For more information on the application process and closing dates, see the How to apply webpage. If you're still having problems, please contact us for assistance.

    Pathways

    Upon completion of the Graduate Certificate of Data Analytics, you could use the credit points you’ve earned to enter into further study, including:

    Contact information

    Our friendly advisers are available to speak to you one-on-one about your study options, support services and how we can help you further your career.

    Careers

    Career outcomes

    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.
    Communication 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.
    Digital literacy Use digital media to locate and collect information to prepare for data analysis.
    Critical thinking Use the frameworks of logical and analytical thinking to evaluate data analytics information and user requirements.
    Problem solving Design solutions for automating data analysis processes by applying foundational technical knowledge and tools.
    Self-management Demonstrate the ability to work autonomously in order to meet requirements.
    Teamwork Not applicable
    Global citizenship Engage in professional and ethical behaviour in the collection, processing, and presentation of data.

    Approved by Faculty Board 6 September 2018