Data Visualisation - Online
Data Visualisation (L9, 10 ECTS)
This module is aimed at manufacturing and process engineers, and other relevant industry professionals who work with large amounts of data on a regular basis.
The module aims are:
• To improve participants visual and design awareness by harnessing their natural ability to recognise visual patterns within data retrieved from in-house or work related data sources
• To strengthen design approaches and methodologies for interpreting data in visually accessible and stimulating ways for industry professionals
• To help industry professionals understand and present their data more effectively therefore allowing them to react decisively and quickly to correct challenges in their work environment
What modules will I study?
Week One: Introduction to data visualisation
Definitions / historical perspective / data visualisation / information design / visual storytelling / key elements of effective data visualisation / case studies
Week Two: Visual storytelling
Audience / intention / meaning and significance / visual storytelling / case studies
Week Three and Four: Approaches to data visualisation
Design convention / using colour / typography / space hierarchy / key examples
Weeks Four to Eight: Self-initiated project
Each week for the duration of the project, there will be a specific time set aside to avail of tutorial advice online. Tutorial times will have to be arranged in advance.
What are the entry requirements?
Applicants must possess a primary honours degree or equivalent.
Recognition of Prior Experiential Learning (RPL) will be granted based on relevant experience and training in accordance with LIT's RPL policy.
This is a level 09 Msc. Special Purpose Award. It is expected that candidates would have prior experience working with technology and have a working knowledge of relevant data software.
Application Deadline: TBC
Register Your Interest: https://lit.ie/Register-Your-Interest?coursecode=LC_ADTVP_RCS
This course is a mix of talks, workshops on the contemporary approaches to data visualisation. Participants will learn to create their own data and understand key theories in the interpretation of data visualisation.
Each session will be delivered online on 10.00am – 1.00pm
Teaching Sessions (Weeks One – Four) The teaching sessions will be online webinars and include a combination of talks along with discussions and workshops. The talks will be available online for those who wish to view them later or can't make the session. However, we would encourage all participants to engage online with the Thursday morning sessions as there will be an opportunity to ask questions and set aside that time in the week for the course.
Project Sessions (Weeks Five – Eight) These are weekly project tutorial sessions are 15 mins conducted via Zoom or MS Teams with each participant.
Presentation Session (Week Nine) Each participant will be given 15 mins to present their project via Zoom or MS Teams
Each 5 credits will normally equate to approximately 100 Total Learning Hours. Total Learning Hours includes the time you spend in class (lectures, tutorials, practical elements) and the time you spend completing work outside of college. The balance between these two varies by discipline, and by level of study. You should bear in mind that the workload will increase at particular times e.g. when assignments are due.