At the end of this learning activity, the student will know the fundamental concepts underlying information visualization. They will be able to assess the relevance of visualisation techniques in the data science pipeline. They will be able to describe the physiological aspects involved and their impact on the effectiveness of a visualisation. He/she will master a catalogue of visualization techniques, as well as the importance of interactive techniques in the creation of visualizations.
The Information Visualisation course aims to enable students to apply recent concepts in information visualisation, both in terms of visualisation techniques and interaction techniques.
The assessment consists of a practical part, based on the work done during the semester.
• Munzner, Tamara. Visualization analysis and design. CRC Press, 2014. • Yau, Nathan. Visualize this! John Wiley & Sons, 2012.
| Training | Study programme | Block | Credits | Mandatory |
|---|---|---|---|---|
| Master in Mathematics, Professional focus in Data Science | Standard | 0 | 4 | |
| Master in Physics, Professional focus in Physics and Data | Standard | 0 | 4 | |
| Certificat d'université d'Executive Master en Data Science | Standard | 0 | 4 | |
| Master in Computer Science, Professional focus in Data Science | Standard | 0 | 5 | |
| Master in Business Engineering, Professional focus in Data Science | Standard | 0 | 4 | |
| Master in Physics, Professional focus in Physics and Data | Standard | 1 | 4 | |
| Certificat d'université d'Executive Master en Data Science | Standard | 1 | 4 | |
| Master in Computer Science, Professional focus in Data Science | Standard | 1 | 5 | |
| Master in Business Engineering, Professional focus in Data Science | Standard | 1 | 4 | |
| Master in Mathematics, Professional focus in Data Science | Standard | 2 | 4 |