Note from June 29, 2020
Although we do not yet know how long the social distancing related to the Covid-19 pandemic will last, and regardless of the changes that had to be made in the evaluation of the June 2020 session in relation to what is provided for in this learning unit description, new learnig unit evaluation methods may still be adopted by the teachers; details of these methods have been - or will be - communicated to the students by the teachers, as soon as possible.
Although we do not yet know how long the social distancing related to the Covid-19 pandemic will last, and regardless of the changes that had to be made in the evaluation of the June 2020 session in relation to what is provided for in this learning unit description, new learnig unit evaluation methods may still be adopted by the teachers; details of these methods have been - or will be - communicated to the students by the teachers, as soon as possible.
5 credits
30.0 h + 30.0 h
Q1
Teacher(s)
Lee John;
Language
English
Content
· What and why information visualisation?
· Data abstraction: types of data and of datasets
· Which visualisation for which task?
· Validating visualisations
· Display and ocular perception
· Visualisation channels (colour, size, shape, angle, ...)
· Tabular data: lists, matrices, tensors
· Spatial data: scalar, vector and tensor fields
· Networks and trees
· Link between machine learning and visualisation: clustering, dimensionality reduction, graph embedding
· Interactive visualisation
· Multiple views
· Advanced topics in visualisation
· Data abstraction: types of data and of datasets
· Which visualisation for which task?
· Validating visualisations
· Display and ocular perception
· Visualisation channels (colour, size, shape, angle, ...)
· Tabular data: lists, matrices, tensors
· Spatial data: scalar, vector and tensor fields
· Networks and trees
· Link between machine learning and visualisation: clustering, dimensionality reduction, graph embedding
· Interactive visualisation
· Multiple views
· Advanced topics in visualisation
Teaching methods
Lectures, practical sessions on computers, project
Evaluation methods
Oral Exam
Online resources
Moodle page of the course: https://moodleucl.uclouvain.be/course/view.php?id=12042
Bibliography
Visualization analysis & Design, Tamara Munzner, CRC Press, 2015.
Teaching materials
- Slides of the course, available on Moodle
Faculty or entity
EPL
