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Data Visualisation

An invaluable course for anyone involved in the collection, analysis or interpretation of data, as well as those responsible for communicating data.

Data Visualisation is effectively communicating information through a graphical means. This course aims to provide an understanding of the theory underpinning the field of data visualisation and to provide an introduction to the practicalities of creating effective graphical representations of data.

The course is suitable for individuals involved in the collection, analysis or interpretation of data, as well as for those responsible for the communication of data to a range of audiences. It is not necessary to have a technical background in data analysis to benefit from this course.

Entry requirements

Minimum Entry Requirements
• Leaving Certificate Examination or equivalent (NFQ Level 5).
• Applicants without this may be considered based on their prior experience and learning through our RPL (Recognition of Prior Learning) process.


4 days: 27 + 28 Sept and 8 + 9 Nov (9.30am – 5pm)

Number of credits


Careers or further progression

Future careers
This course broadens the skills of anyone working with data in a wide variety of organisations, including manufacturing, financial services, market research and the broader public sector. Successful graduates of the course can apply for a related Masters Degree course or for a suitable research postgraduate Masters Degree in IADT (if you already hold an Honours Degree).

If you do not hold an Honours Degree, you may be interested in our undergraduate degrees in Applied Psychology, Creative Computing and Creative Media Technologies.

Further enquiries

Cyril Connolly, Course Co-ordinator
E -

Subjects taught

What topics will I study?
• Representing data in one, two + higher dimensions
• Apply best practice principles for the graphical communication of data
• Explore data sets using dynamic + interactive software tools
• History, current trends + emerging themes in data visualisation.

This course combines a mix of lectures, practical work, and informal discussions around important topics in data visualisation. Students will be required to critique existing visualisations, find interesting data sets, and create their own visualisations.

Assessment method

Two written pieces of continuous assessment work.

Application date

Application Date: 22 August 2018, 4pm.

Course fee


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