Skip to main content
INTERESTED IN STUDYING WITH THE UNIVERSITY OF ADELAIDE?
I’m interested in…

Graduate Diploma in Data Science (Applied)

Duration

1.4 years (Part­Time)

SATAC Code

GDDSA

Program price (2020 pricing)

$3,828 per course

Program Overview

Data is everywhere, and understanding it is a key skill that could set you apart in a rapidly evolving world. Studying a postgraduate data science program can teach you a range of applied data science skills, such as how to code, handle data, manage visualisations, and master a vast range of problem-solving abilities.

Our Graduate Diploma in Data Science (Applied) gives students the opportunity to add to their existing qualifications. This 100% online postgraduate data science program is designed to develop the knowledge needed to bridge the gap between recognising the importance of data and knowing how to put data science techniques into practice.

What could your future look like?

Upon graduating from our 100% online Graduate Diploma in Data Science (Applied), you’ll have the skills and knowledge to advance your career in diverse industries, such as business, tech, healthcare and e-commerce.

The arrival of the big data era has increased the value of data science qualifications in terms of future job prospects and wage growth. Attaining formal recognition of your skills by studying applied data science online will ensure you have the expertise to remain at the forefront of the data science revolution.

As this program focuses on applied data science, it takes a hands-approach to skill development. It will advance your technical know-how and give you the skills to find solutions for a wide range of problems.

What will you learn?

Our Graduate Diploma in Data Science (Applied), develops students’ knowledge across a range of courses. Each area covered can be added to your existing skill set to ensure you’re up to date with the latest innovations in data science. You’ll learn how to:

  • Apply, evaluate and use the principles of applied data science in real-world contexts, including the specific requirements needed for large-scale data analysis
  • Demonstrate an understanding of the technical practice, management and strategic impact of data science, and its application within industry contexts
  • Apply, evaluate and use best-practice tools, techniques and theory of data science within a range of application domains
  • Adopt and employ professional attitudes, standards and values
  • Use highly effective interpersonal skills to enable empathetic and effective communication.

  • Human and ethical factors in computer science - COMPSCI 7212OL

    You will study two important areas in contemporary computing – human factors and ethical theory and practice – to determine whether your work aligns with definitions of what is right for individuals, companies, and society. By combining two areas of data science, participants will learn how to apply tools and analysis tactics to establish whether the computing tasks they are being asked to perform are fit for purpose in terms of both usage and ethics.

  • Data taming, modelling, and visualisation - DATA 7201OL

    A practical introduction to finding relationships in data using statistical methods, this course covers the principles of taming and tidying data. It familiarises students with:

    • Different types of data
    • Exploratory data analysis
    • Visualisation techniques
    • Data transformation
    • Model fitting and interpretation.

    One of the course’s core aims is to introduce R programming for data science applications through real-world case studies.

  • Foundations of computer science: Python A - COMPSCI 7210OL

    This course will develop your coding and problem-solving skills with a focus on data science principles. You will learn algorithm design and fundamental programming concepts such as:

    • Data selection
    • Iteration and functional decomposition
    • Data abstraction and organisation.

    You will complete this course with the confidence to apply fundamental software development skills including Python programming language, debugging, testing, and other fundamentals of good programming practice.

  • Applied data science - DATA 7202OL

    An introduction to the role and application of data science in modern organisations and societies, this course includes processes for data collection, analysis, verification and validation. Case studies will be used to demonstrate current best practice and common pitfalls.

  • Foundations of computer science: Python B - COMPSCI 7211OL

    This course introduces fundamental concepts of data science applications in Python. You will develop several applied data science skills, including:

    • Object-oriented fundamentals, methods, and classes
    • Algorithms and problem-solving processes and strategies
    • Computational complexity of algorithms
    • Software development tools and techniques.
  • Applications of data science - DATA 7301OL

    This course provides a practical introduction to data modelling, analysis and prediction using contemporary software packages. You will also be given an overview of common data science techniques and their implementation in software libraries.

  • Mathematical foundations of data science - MATHS 7027OL

    You will learn fundamental mathematical concepts relevant to computer science in this course. It also provides a basis for further postgraduate study in the following fields:

    • Data science
    • Statistical machine learning
    • Cyber security
  • Real data: Modern methods for finding hidden patterns - DATA 7302OL

    Building on skills acquired in the DATA7201 Data taming, modelling and visualisation course, this course introduces advanced techniques for extracting meaningful information from real-world datasets. It covers a range of methods, including:

    • Generalised linear models
    • Classification
    • Advanced regression techniques
    • Unsupervised statistical learning.

    This course will also teach advanced R programming techniques for data science, as well as data-wrangling techniques.

The Graduate Diploma in Data Science is perfect for students who have recognised the value in learning applied data science skills. This qualification enables students to leverage their current skills and expertise in complementary disciplines, such as business analytics, program management and technology.

As more organisations come to rely on applied data science techniques, the demand for qualified data scientists will inevitably rise. According to the LinkedIn 2017 U.S. Emerging Jobs Report, data science roles have grown over 650% since 2012, with 2.7 million new jobs forecasted globally by 2020 and 11.5 million jobs expected by 2026. These statistics leave no doubt that the future is looking bright for data scientists. 

Salary Expectations 

The Graduate Diploma in Data Science offers excellent return on investment. The more experience a data scientist can offer, the greater their earning potential. In a study on salary expectations in the data science field, Payscale.com found that entry level data scientists with 1 – 4 years’ experience earn AU$91,782 on average, while mid-career data scientists with 5-9 years of experience typically earn around AU$111,100. Average earnings for data scientists with 10+ years’ experience jumped to AU$121,052. 

With salaries set to increase even further, a postgraduate qualification is a great way to make the most of your earning potential as a data scientist.

To be eligible for the Graduate Diploma in Data Science (Applied), you will need an undergraduate Bachelor's degree or equivalent in any discipline with a minimum GPA of 4.5. 

You will also need to have completed SACE Stage 2 Mathematical Methods or equivalent.