DL103- Certificate Data Visualisation
This course is currently offered in collaboration with Creative Futures Academy (CFA). CFA is a ground-breaking partnership between: The National College of Art and Design, University College Dublin, and the Institute of Art, Design + Technology. Our tailored programmes and micro courses offer access to expertise and networks across the three leading creative institutions and our industry partners. Learn with us as we experiment, innovate and respond to change.
What will I be doing?
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 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.
You will be required to complete two assignments during the year, but there are no written examinations.
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 course 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, Creative Computing and Creative Media Technologies.
What topics will I study?
- Representing data in one, two and higher dimensions including the visualisation of spatial data.
- 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.
A number of software applications will be introduced including Tableau and R based data visualisation libraries including ggplot2. No prior knowledge of these software applications will be assumed.