Introduction to programming with R for data analysis
R’s potential for data analysis, statistics and visualization, combined with the fact that it is free software, make it a natural ally for the processing of big data, both in scientific circles and in business. This training program is intended for people who would like to learn R and be able to program simple functions with this language.
Training offered in French
R is ranked 5th in the 2019 Institute of Electrical and Electronics Engineers (IEEE) annual ranking of programming languages. According to a 2018 study by the job search site Indeed, the demand for engineers or data analysts familiar with the statistical programming language R is growing very rapidly.
R’s potential for data analysis, statistics and visualization, combined with the fact that it is free software, make it a natural ally for the processing of big data, both in scientific circles and in business.
This training program is intended for people who would like to learn R and be able to program simple functions with this language.
Training program presented by
Main objective
Use the R language to perform data analysis and to develop your own tools.
Specific objectives
Upon completion of this training program, the participant will be able to:
- Use the R statistical environment interactively
- Use the R programming language to solve real everyday problems
- Perform a full data analysis in R
Contents
- Presentation of R and the development environment
- Creation and modification of R script files
- Basics of programming with R
- R data structures and application functions
- Data import and export
- Packages
- Simple graphics
Instructor
Full Professor, Faculty of Science and Engineering, Université Laval
Vincent Goulet is a professor at the School of Actuarial Science at Université Laval. He has taught R programming for almost 15 years, and drew upon this experience to prepare the free document “Programming with R”. He is the author of Actuar, the first R package dedicated specifically to actuarial science and extreme value distributions. He began using R when the version number still started with a 0, making him a pioneer with a valuable expertise in this field.
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