Objectives
When algorithms struggle to highlight trends and weak signals in massive or complex data, a visualisation is sometimes more relevant. Choosing the most appropriate one is an important step in data analysis.
Programme
-Understanding the history of visualisation and graphic representations
-create visualisations adapted to the data and consistent with graphical semiology
-understanding and exploiting the cognitive mechanisms involved in graphic representations
-prototyping visualisations using R and its graphics libraries
-create interactive web dashboards to share visualisations
Carry out and deliver an in-depth exploratory analysis of a dataset
