Descriptif
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.
Diplôme(s) concerné(s)
- Diplôme d'ingénieur de l'Ecole polytechnique
- Innovation Technologique : ingénierie et entrepreneuriat
Parcours de rattachement
Format des notes
Numérique sur 20Littérale/grade réduitPour les étudiants du diplôme Diplôme d'ingénieur de l'Ecole polytechnique
Le rattrapage est autorisé- Crédits ECTS acquis : 5 ECTS
La note obtenue rentre dans le calcul de votre GPA.
Pour les étudiants du diplôme Innovation Technologique : ingénierie et entrepreneuriat
Le rattrapage est autorisé- Crédits ECTS acquis : 4 ECTS
La note obtenue rentre dans le calcul de votre GPA.