R is not only an open-source, freely available and widely used programming language and interactive environment for data analysis, but one of its main attractions is to give easy access to the most powerful methods and graphical techniques for understanding data. R benefits from a large community of passionate contributors, including prominent researchers, who implement the latest developments and newest results in statistics, data computing, and statistics for applications. This makes R one of the most popular software packages for data scientists, and its use is booming in academia, business, and machine learning challenges.
The aim of this course is to give students a solid foundation to master the amazing capacities of R for statistics and graphics. We begin by examining some fundamental principles and essential programming needed for all data analysis. Next, we look at the exciting field of data exploration and present classical statistical models and learning methods, including some recently introduced techniques. We will analyse and model data, with a particular importance given to visualization and interactive features of R, which are key to communicate results.
Format des notesNumérique sur 20Littérale/grade réduit
Pour les étudiants du diplôme Diplôme d'ingénieur de l'Ecole polytechniqueL'UE est acquise si note finale transposée >= C
- Crédits ECTS acquis : 5 ECTS
La note obtenue rentre dans le calcul de votre GPA.