Free Online Course on Big Data: Data Visualisation

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Queensland University of Technology (QUT) is offering Data Visualisation Online Course. This free online course will provide you with an informative introduction to the methods, tools and processes involved in visualising big data.

Data visualisation is vital in bridging the gap between data and decisions. Discover the methods, tools and processes involved. The course will start on June 27, 2016.

Course At A Glance

Length: 2 weeks
Effort: 2 hours pw
Subject: Data Visualisation
Institution: Queensland University of Technology (QUT) and FutureLearn
Languages: English
Price: Free
Certificate Available: Yes
Session: Starts on June 27, 2016

Providers' Details

Queensland University of Technology (QUT) is a leading Australian university ranked in the top two percent of universities worldwide in the 2015-16 Times Higher Education World University Rankings. Our courses are in high demand, and our graduates include eight Rhodes Scholars, five of these awarded in the past six years. We are a connected, relevant and collaborative institution that seeks to solve real-world challenges.

About This 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.

Why Take This Course?

This course is part of the Big Data Analytics program, which will enable you to gain the big data analytics skills that are in demand today.

Learning Outcomes

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:

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


Tomasz Bednarz

He is 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

He is a designer, digital artist, and Ph.D. candidate. My research and creative practice bridges art, science, creative code, big data, emerging technologies, and the everyday user.

Miles McBain

He is a Research Associate in the BRAG group at QUT. I have a background in software development and masters degree in Mathematics. R is my platform of choice for data analysis.

Samuel Rathmanner

He is a Computer Scientist from the Australian National University with a particular interest in machine learning and artificial intelligence.

Matthew Sutton

He is am a Ph.D. student with research interests in genomics, operations research, big data and machine learning.

Steven Psaltis

He is 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


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

University 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.
  • 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.

How To Join This Course

  • Go to the course website
  • Sign Up At FutureLearn
  • Select a course and Join
  • Once a course has started, applicant will be able to access the course material
  • After the start date, students will be able to access the course by following the Go To Course link on My Courses page.
  • Applicants can buy, to show that they have completed a FutureLearn course.
  • On some FutureLearn courses, learners will be able to pay to take an exam to qualify for a Statement of Attainment. (These are university-branded, printed certificates that provide proof of learning on the course topic(s)).

Apply Now

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