Introduction to Data Analytics in R

About

Many companies have access to mountains of data and increasingly recognize the importance of turning these data into insights. This leads to a pressing need for data analysts and explains the growing popularity of data analytics software. The current course introduces participants to one specific software package, namely the open-source programming environment R, and the accompanying developers’ environment R Studio. 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) working with data in R (management, analysis, and visualization); and (iii) control flow and programming in R.

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. The course is concentrated in one week, with three contact hours on each day of that week. The sessions are a mix of (interactive) lectures and tutorial meetings. During the lectures, we learn new material, whereas during the tutorial meetings, we discuss assignments to train our understanding of the studied material.

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

By the end of the course, the following learning outcomes are expected for students:
• To get to know the open-source language R and the accompanying developers’ environment RStudio.
• To become familiar with the basic objects and operations in R.
• To learn to work with data in R.
• To get introduced to programming and algorithmic thinking.

Fee info