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.
Applications for 2021/22 will open Autumn 2021

 

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.