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
