Bayes Centre

Data Visualisation for Professionals

This online credit-bearing course teaches professionals how to visually explore data and how to criticise, design and implement data visualisations. It teaches the fundamentals of human perception and data visualisation; exploratory data analysis; the importance of interaction in exploration; techniques and tools for data visualisation; storytelling and communication.

Course Summary

This course teaches general knowledge about the theory, application, design, and evaluation of visualisations. The goal of the course is to enable you to understand the potential of visualisations for exploration, analysis and communication. It will enable you to describe a visualisation problem, to explore the data using data visualisation, to discuss and design appropriate visualisation concepts, and to implement and critically reflect on them.

The course targets professionals working in finance, sport, the creative industries, journalism, education and the public sector. It is designed for an interdisciplinary audience, targeting people with a background in design, data analysis, and other areas. General programming skills are not required but  those with a good understanding of JavaScript or Python can learn how to use visualisation libraries such as D3.js, https://d3js.org

The delivery of this course is intended to be as flexible as possible to accomodate your work schedule. Course content is delivered through recorded online video lectures, suggested readings, online tutorials, quizzes, exercises that can be handed in to obtain feedback and optional on-campus workshops for those who can attend.

For more information, please visit: https://datavis-online.github.io/

Course Delivery Information

Start Date: To be confirmed
Course Duration:

10 weeks

Total Hours: 100 (Lecture Hours 22; Tutorial Hours 6; Independent Study Hours 72) 
Method of Assessment: Coursework 100%
Level:  This is an introductory Masters-level course (SCQF Level 11). It provides foundational skills and/or an overview of the subject – no prior knowledge is needed. Masters-level courses are relatively intensive and require independent learning, critical thinking, analysis and reflection.

Dates for the next iteration of this course have yet to be confirmed but please sign up to our mailing list to ensure you are kept up to date on when this course is next running.

Entry Requirements

A UK 2:1 honours degree, or its international equivalent.  

If you do not meet the minimum academic requirement, you may still be considered if you have relevant work experience preferably with:

  • a basic knowledge of programming in Python or JavaScript.
  • experience using Adobe Illustrator or an equivalent
  • experience creating basic visualisations in Excel, Tableu or PowerBI

If you are unsure whether you meet these criteria please send your CV to bayes-training@ed.ac.uk

Check whether your international qualifications meet our general entry requirements:

English Language Requirements

You must be comfortable studying and learning in English if it is not your first language.

Course Fees and Funding

Course fees for 21/22 are £960, but funded places are available for people employed, unemployed or furloughed in Scotland who meet Scottish Funding Council elgibility criteria.

Determining eligibility for a funded place for upskilling takes a number of things into account, including fee status, but also location of employer. SFC provide guidance specifically for upskilling courses:

“Courses/provision is open to all Scottish-domiciled/’home fee’ students, which is consistent with SFC’s policy for core funded student places. Students from the rest of the UK (rUK) are not normally considered eligible for SFC funding. If however a university is working with a Scottish/UK employer which has a physical presence or operating in Scotland, rUK employees of that employer would be eligible.”

Organisations like UKCISA, and the University, provide guidance on how to determine your fee status:

If your fee status is Scotland Fee Rate, RUK Fee Rate, or EU-EEA Pre/Settled Scotland Fee rate, you may be eligible for a funded upskilling place. To determine this we will look at your fee status, residency information and, where relevant, details of your employer, to confirm whether the employer is based in, or has a significant presence, in Scotland.

Funding eligibility will be assessed at the point of each application for each course; you may be asked to provide further information if you do not meet the general residence conditions. Please email us at bayes-training@ed.ac.uk if you would like to discuss your funding eligibility before applying.

Please note that full-time students (including full-time PhD students) are not eligible for funding.