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Free online course

Big Data: Data Visualisation

Data visualisation is vital in bridging the gap between data and decisions. Discover the methods, tools and processes involved.


  • Access to the course for its duration + 14 days, starting from when you join
  • No certificate


  • Unlimited access to the course for as long as it exists on FutureLearn
  • A Certificate of Achievement when you complete the course

Find out more

Big Data: Data Visualisation

Why join the course?

Data visualisation is an important visual method for effective communication and analysing large datasets. Through data visualisations we are able to draw conclusions from data that sometimes are not immediately obvious, and interact with the data in an entirely different way.

Get an introduction to big data visualisation

This free online course will provide you with an informative introduction to the methods, tools and processes involved in visualising big data. It has six elements:

  1. Introduction to visualisation
  2. Information visualisation
  3. Scientific visualisation
  4. Visualisation tools
  5. Design approaches for visualisation
  6. Visualisation for communication

Visualise real-world big data problems

We have designed the course around case studies from different fields. This way, you will be able to identify visualisation application areas and learn how to produce visualisations that help you to better understand real-world big data problems.

We will also take the time to examine briefly the use of visualisation throughout history dating back as far as 17,000 BC.

Continue learning with the Big Data Analytics program

This course is one of four in the Big Data Analytics program on FutureLearn from the ARC Centre of Excellence for Mathematical and Statistical Frontiers at Queensland University of Technology (QUT).

The program enables you to understand how big data is collected and managed, before exploring statistical inference, machine learning, mathematical modelling and data visualisation.

When you complete all four courses and buy a Certificate of Achievement for each, you will earn a FutureLearn Award as proof of completing the program of study.


QUT would like to thank the following content contributors:

  • Tomasz Bednarz
  • Pamela Burrage
  • Phil Gough
  • Miles McBain
  • Steve Psaltis

Skip to 0 minutes and 7 secondsHi everyone and welcome to our Big Data Analytics collection of courses. My name is Kerrie Mengersen. Imagine you’re a scientist in a lab, investigating a new strain of bacteria that’s extremely harmful and potentially deadly. As a scientist you’re naturally curious, however there’s no way you would want to get too close to the bacteria and risk being contaminated. So how can you examine these bacteria closely, without potentially risking your health? Real life situations such as this have been resolved through the use of visualisations. Instead of physical interaction with the bacteria, scientists have created a virtual playground where they can effectively interact and examine bacteria without being at risk.

Skip to 0 minutes and 55 seconds Creating good visualisations not only produces something that looks nice, it helps us uncover and interact with information that might not have been immediately obvious. In this course we offer a unique insight into different visual techniques for analysing Big Data. We help you understand some different tools for creating effective visualisations, and show you examples where visualisations have been incredibly effective - such as the bacteria example. We’ve created this course to share with you the multi-lensed approach we use at ACEMS that enables us to create new insights and ways of thinking around the Big Data space. We’re excited and we hope you are too.

What topics will you cover?

  • Introduction to visualisation
  • Information visualisation
  • Scientific visualisation
  • Visualisation tools
  • Design approaches for visualisation
  • Visualisation for communication

When would you like to start?

  • Date to be announced

What will you achieve?

  • Explore big data frameworks
  • Demonstrate an integrated approach to big data
  • Develop an awareness of how to participate effectively in a team working with big data experts

Who is the course for?

There are many software tools for data visualisation and visual analytics, and the list is still growing.

In this course we will use a variety of tools, so that you can become comfortable with engaging with different software packages and gain confidence in trialling new packages that may better meet your particular needs.

We will be using the following tools. Please review the product websites below to ensure your system meets the minimum requirements:

  • Tableau: as the free trial period is 2 weeks, please do not start your free trial ahead of the course start date.
  • MATLAB Online: a license will be provided for the duration of the course.
  • D3.js: a JavaScript library available under BSD license.

If you don’t have access to all of these tools, you can still be an effective learner in this course. You can see what they can do, and use the tools later or investigate the use of other tools that might be more available to you.

Who will you learn with?

Tomasz Bednarz

I’m an Associate Professor at QUT interested in visualisation and interactive techniques, computer graphics, computational and simulation sciences, machine learning, and visual and big data analytics.

Phil Gough

I am a designer, digital artist, and PhD candidate. My research and creative practice bridges art, science, creative code, big data, emerging technologies, and the everyday user.

Samuel Rathmanner

Hi, I am a Computer Scientist from the Australian National University with a particular interest in machine learning and artificial intelligence.

Steven Psaltis

I'm a Postdoctoral Fellow in the ARC Centre of Excellence for Mathematical and Statistical Frontiers at QUT. I'm interested in numerical simulation of physical systems, gpu computing and visualisation

Anthony (Ace) Ebert

I'm a statistics PhD student at QUT. I'm interested in Bayesian analysis and Queueing theory. I script in R.

Who developed the course?

QUT is a leading Australian university ranked in the top 2% of universities worldwide by the 2015-16 Times Higher Education World University Rankings. Located in Brisbane, it attracts 47,000 students.


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Buy a personalised, digital and printed certificate and transcript

You can buy a Certificate of Achievement for this course — a personalised certificate and transcript in both digital and printed formats, to prove what you’ve learnt. A Statement of Participation is also available for this course.

Certificate of Achievement + transcript £49.00

Statement of Participation £34.00

Estimate prices in preferred currency

Charges to your account will be made in GBP. Prices in local currency are provided as a convenience and are only an estimate based on current exchange rates.