Introduction to Data Analytics in R

Many companies have access to mountains of data and increasingly recognize the importance of turning these data into insights. This development leads to a pressing need for data analysts and explains the growing popularity of data analytics software. This course introduces participants to one such software package, namely the open-source programming environment R. Through lectures and interactive, assignment-based, tutorials, students will be introduced to three crucial aspects of data analytics in R: (i) basic objects and operations in R; (ii) flow control and programming in R; and (iii) working with data in R (management, analysis, and visualization).

The course offers a good foundation for individuals who intend to get involved in data analytics (e.g., start a business intelligence/analytics master program or plan to take other, independent data analytics courses), but have little or no coding/programming experience. The skills acquired in this course are also useful for data analytics in syntax-driven environments other than R.

Course leader

Bram Foubert

Target group

▪ Knowledge of algebra (high-school level)
▪ Familiarity with datasets (e.g. in Excel or SPSS)
▪ No prior coding or programming experience needed

Course aim

▪ Get to know the open-source language R and the accompanying developers’ environment RStudio;
▪ Become familiar with the basic objects and operations in R;
▪ Get introduced to programming and algorithmic thinking;
▪ Learn to work with data in R.