Statistical Programming and Data Science

Training in statistical programming and data analysis

Statistical programming languages ​​make it possible to manage datasets, produce analyzes and build elaborate charts. For example, the R language is one of the languages ​​of choice in machine learning, it is supported by a large community of researchers and contributors around the world. The R environment is of the open source type. This training aims to provide the bases required to start analysis, programming and data mining projects in R.

Training objectives

  • Perform common operations on a data table (sort, filter, select, merge, etc.)
  • Import, clean, organize and export data files
  • Create simple charts to visualize the data
  • Write reusable custom functions
  • Know how to search for help in the R community

Target audience

  • Anyone wishing to use a programming language to manipulate data and generate reports.
  • This course requires knowledge of the basics of computer programming, regardless of the language.


  • Virtual or in-person
  • 60% theory and 40% practical (bring your dataset for exercises)​
  • Duration: 16 hours​ (or 4x 4 hours)


  • The R environment and RStudio
  • Types of variables
  • Vectors, matrices and dataframes, selection of subsets
  • Basic operations and logic
  • Structure of if-else statements and for-while loops
  • Reusable custom function structure
  • Concept of vectorized function and implicit loop
  • How to find help on the web
  • Practical workshops and exercises: importing a data file; obtain descriptive statistics; build simple charts; do a Pareto analysis; write a custom function and call it; copy and paste results and charts to other software


  • Be familiar with computer tools in general
  • Ideally have use cases in mind
  • Have installed the R software
  • Have installed the free version of RStudio

This training is pratical, theoretical elements are very limited. For more informations or to book your training, please contact us!

⤶ (back to Data Analytics page)