“The best programs are written so that computing machines can perform them quickly and so that human beings can understand them clearly.” – Donald Knuth


This course aims to provide you with the basic skills to write computer programs that are efficient and clearly communicated solutions. The main focus will be on programming in the field of data science, which is particularly useful for researchers, as it allows you to turn raw data into understanding, insight, and knowledge. The goal of this course is to help you learn the most important tools in the R programming language that will allow you to do data science.


After this course you will be able to

  • Explain the fundamentals of programming (in R)
  • Solve problems by programming them in R
  • Import, tidy, and transform data for further analysis
  • Use models and visualization to explore your data
  • Create reproducible solutions in R that can be used by others


The course consists of practical three-hour sessions, where theory is interspersed with exercises to get hands-on experience with R. The course is graded based on the exercises that are handed in during the course. The course has a high focus on independent learning, and the students are expected to program the exercises also outside the practical sessions.


The course starts from the very beginning; no prior programming experience is required.


Each week a programming assignment needs to be handed in during the course. The grade of the course will be the average of the grades for the individual assignments.


Wickham, H., & Grolemund, G. (2016). R for Data Science. O'Reilly (available for free online at

Additional info

The timetable for this course can be found in the EUR course guide.

ERIM PhD candidates and Research Master students can register for this course via Osiris Student.

External (non-ERIM) participants are welcome to this course. To register, please fill in the registration form and e-mail it to the ERIM Doctoral Office by four weeks prior to the start of the course. For external participants, the course fee is 260 euro per ECTS credit.