Graduate Diploma of Data Analytics

COURSE (DOMESTIC STUDENTS)

Overview

The Graduate Diploma of Data Analytics provides you with the specialist knowledge required to formulate solutions to complex data problems across a range of business settings – turning raw data sets into meaningful information to better guide business decisions.

This course aims to prepare you for specialised careers in data analytics by providing you with advanced working knowledge in statistics and data science. You’ll draw on previous studies in IT, computing or related disciplines to focus on the specific application of data analysis in a business setting.

You’ll get an understanding of the various origins of data to be used for analysis, combined with the central approaches and methods to manage, organise and manipulate such data, within regulatory, ethical and security constraints. You’ll learn fundamental aspects of data science, modern methods, techniques and applications of data science.

You’ll learn how to identify problems and understand the various techniques and methods that can be used to solve them. You’ll be able to extract meaning from, make sense of, and draw conclusions from data. These skills will enable you to approach and represent different types of data, and to perform data analysis and statistical inference tasks of interest.

Data security and its governance have now become key issues for all organisations. As such, the various ethical, regulatory and governance aspects of analytics systems will be covered. Potential privacy and security issues associated with large data sets and the results obtained from analytics on such data are examined in detail.

As a graduate, you’ll be ready for a career as a software developer, computer systems analyst/architect/engineer, marketing manager, market research analyst and marketing specialist, management analyst, web developer, network and computer systems administrator, IT project manager, or computer or IT research scientist.

Units in the course may include assessment hurdle requirements.

Read More VIEW INTERNATIONAL COURSE INFORMATION

Key facts

Duration

1 year full-time or part-time equivalent

Campuses

Offered at Burwood (Melbourne) Cloud (online)

Trimester 1

  • Start date: March
  • Available at:
    • Burwood (Melbourne)
    • Cloud Campus

Trimester 2

  • Start date: July
  • Available at:
    • Burwood (Melbourne)
    • Cloud Campus

Trimester 3

  • Start date: November
  • Available at:
    • Burwood (Melbourne)
    • Cloud Campus

Key information

Award granted

Graduate Diploma of Data Analytics

Year

2017 course information

Estimated tuition fee - full-fee paying place

$26,280 for 1 yr full-time - Full-fee paying place
Learn more about fees and your options for paying.

Deakin code

S677

CRICOS code

089187D

Level

Postgraduate (Graduate Certificate and Graduate Diploma)

Approval status

This course is approved by the University under the Higher Education Standards Framework.

Australian Quality Framework (AQF) recognition

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

Entry requirements

Deakin University offers admission to postgraduate courses through a number of Admission categories.
In all categories of admission, selection is based primarily on academic merit as indicated by an applicant's previous academic record.
For more information on the Admission Criteria and Selection Policy visit The Guide.

Bachelor degree in a related discipline, being analytics, information technology or computing.

Career outcomes

Graduates of this course may find careers as software developers, computer systems analysts/architects/engineers, marketing managers, market research analysts and marketing specialists, management analysts, web developers, network and computer systems administrators, IT project managers, computer and IT research scientists.

Course learning outcomes

Deakin Graduate Learning Outcomes (DGLOs)

Course Learning Outcomes (CLOs)

1. Discipline-specific knowledge and capabilities: appropriate to the level of study related to a discipline or profession.

  • Develop specialised knowledge of data analytics concepts and technologies to solutions based on specifications and user requirements.

 

2. Communication: using oral, written and interpersonal communication to inform, motivate and effect change.

  • 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.

 

3. Digital literacy: using technologies to find, use and disseminate information.

  • Use digital media to locate, collect and evaluate information from technical channels and apply information to design approaches and solutions that meet user requirements.

4. Critical thinking: evaluating information using critical and analytical thinking and judgment.

  • Use the frameworks of logical and analytical thinking to evaluate data analytics information, technical problems and user requirements, and develop approaches to identify solutions.

 

5. Problem solving: creating solutions to authentic (real world and ill-defined) problems.

  • Design solutions for automating data analysis processes by investigating technical and business problems; design and propose alternative solutions that improve services and user experiences.

6. Self-management: working and learning independently, and taking responsibility for personal actions.

  • Demonstrate the ability to work in a professional manner, learn autonomously and responsibly in order to identify and meet development needs.

7. Teamwork: working and learning with others from different disciplines and backgrounds.

  • Not applicable

8. Global citizenship: engaging ethically and productively in the professional context and with diverse communities and cultures in a global context.

  • Engage in professional and ethical behaviour in the design of data analytics systems, in a global context, in collaboration with diverse communities and cultures.

Approved by Faculty Board 14 July 2016

Course Structure

To complete the Graduate Diploma of Data Analytics, students must attain 8 credit points. Most units (think of units as ‘subjects’) are equal to 1 credit point. So that means in order to gain 8 credit points, you’ll need to study 8 units (AKA ‘subjects’) over your entire degree. Most students choose to study 4 units per trimester, and usually undertake two trimesters each year.

The 8 credit points include 6 core units (these are compulsory) and 2 level-7 course grouped elective units (you can choose which ones to study from a specified list).

6

Core units

2

Elective units

8

Total units

Core

Year 1 - Trimester 1

  • Statistical Data Analysis SIT741
  • Modern Data Science SIT742
  • Plus two (2) course grouped elective units

    Year 1 - Trimester 2

  • Security and Privacy Issues in Analytics SIT719
  • Machine Learning SIT720
  • Multivariate and Categorical Data Analysis SIT743
  • Practical Machine Learning for Data Science SIT744
  • Electives

    Select the remaining 2 credit points from a range of level 7 SIT/MIS course grouped elective units.

    How to apply

    Apply direct to Deakin

    Applications must be made directly to the University through the Applicant Portal. For information on the application process and closing dates, see the how to apply web page. Please note that closing dates may vary for individual courses.

    Apply through Deakin

    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.

    Register your interest to study at Deakin

    Please complete the Register your interest form to receive further information about our direct application opportunities.

    Course pathways

    Further study options

    S777 Master of Data Analytics

    Credit for Prior Learning

    Am I eligible to receive credit for 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 Credit for Prior Learning System which outlines the credit that may be granted towards a Deakin University degree and how to apply for credit.

    Faculty contact information

    Faculty of Science, Engineering and Built Environment
    School of Information Technology
    Tel 03 9244 6699
    sebe@deakin.edu.au

    www.deakin.edu.au/information-technology

    Fee information

    The tuition fees you pay will depend on the type of fee place you hold. 

    • If you are enrolled in a Commonwealth supported place, your tuition fees are calculated depending on the units you choose.
    • If you are enrolled in a full fee paying place, your tuition fees are calculated depending on the course you choose.

    In both cases, the ‘Estimated tuition fee’ is provided as a guide only based on a typical enrolment of students completing the first year of this course. The cost will vary depending on the units you choose, your study load, the length of your course and any approved Credit for Prior Learning you have.

    Each unit you enrol in has a credit point value. The ‘Estimated tuition fee’ is calculated by adding together 8 credit points of a typical combination of units for that course. Eight credit points is used as it represents a typical full-time enrolment load for a year.

    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 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

    Offered campuses

    Burwood

    Just 30 minutes from the city centre, the Melbourne Burwood Campus is Deakin's thriving metropolitan campus.


    Study online at Cloud Campus

    Students are able to study all or part of this course online. You can study anywhere, anytime through Deakin's Cloud Campus.

    Learn more about studying online and the Cloud Campus

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