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Last year we started with our R Experience at the University of Groningen. Where we taught Marketing and Marketing Intelligence students not only the basics of R and RStudio, but also how to perform data preparation and how to use different modeling techniques. At the beginning of the five courses none of the students ever saw the R language before. At the end they felt comfortable enough to not only perform the steps we showed them, but to also play around with R themselves. For us as teachers that was such a big reward. Which became even better after we saw the way the students evaluated the course; they graded us of a 8.5 out of 10 and everybody would recommend the course to others.

Because both we and them considered this course to be a big success, we went back for a second round this year. And also this time we consider it as a big success with a grade of 8 out of 10 and again everybody would recommend the course to others!

After the second round at the University of Groningen we also taught the R Experience at Eneco, Delta and our Cmotions Talent Academy. The employees of both Eneco and Delta are going to make a switch to R from SAS and SPSS and this is why they needed a kickstart in coding in R. This is exactly why we created the R Experience; it is intended to help people with analysis skills getting familiar and comfortable with the R language.

In a short time we gained a lot of knowledge about R. From the basics to useful tips and tricks. -Eneco

We consider it a job well done since Eneco rewarded our course with an 8.5 out of 10, and Delta with an 8 out of 10! And let’s not forget our Cmotions Talent Academy, these young and enthusiastic students rewarded our course with an 8,6 out of 10. And also in these three groups everybody would recommend our course to others.  We’re so happy to hear all these enthusiastic sounds!

This is now my favorite tool! – Student Talent Academy

Did we make you curious about our R Experience? The course consists of five modules, it starts with an easy introduction in writing R code. In the following modules we’ll go deeper and deeper, where we start with explaining the differences between R and Rstudio and touch topics like importing data and how to use functions. The next module consists of data manipulation and preparation, like outliers, highly correlated predictors, near zero variance and missing values. And in the last module we’ll use caret to show how you could train practically every algorithm you want for classification purposes.

Interested in the R Experience? Contact us!

this article is written by

Jeroen Kromme

Jeanine Schoonemann