Certificate in Data Visualisation هذه الدورة تدرس باللغة الإنجليزية

تفاصيل الدورة

The aim of data visualisation is to effectively communicate 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. 

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. 

The course is suitable for inpiduals 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. 

You will be required to complete two assignments during the year, but there are no written examinations.

Aims and Learning Objectives

What will I be able to do when I graduate?

• This course should broaden the skills of anyone working with data in a wide variety of organisations, including manufacturing, financial services, market research and the broader public sector.  
• If you already hold an Honours Degree you may apply for a related Masters Degree programme or for a suitable research postgraduate Masters Degree in IADT. 
• If you do not hold an Honours Degree, you may be interested in our undergraduate degrees in Applied Psychology and Computing/Multimedia.

What topics will I study?

• Representing data in one, two and higher dimensions
• Apply best practice principles for the graphical communication of data
• Explore data sets using dynamic and interactive software tools
• History, current trends and emerging themes in data visualisation 

What are the entry requirements? 

Leaving Certificate Examination or equivalent (NQF Level 5). Applicants without this can also be considered based on their prior experience and learning (RPL).