The modern world is flooded with data ‒ big data ‒ and it is ruled by artificial intelligence (AI) and machines. All right, this is an exaggeration, but the tendency is there. These rapid changes create a pressing need for professionals who are able to process large amounts of information for decision-making using AI and machine learning approaches. That is why ‒ starting from this academic year ‒ SSE Riga lecturers are devoting a significant amount of their time to teaching students R programming skills.

R is a data analysis software and programming language used by analysts, statisticians and scientists to process and analyse large volumes of data using modern statistical, econometric and machine learning methods. R is one of the most popular programming languages nowadays. Moreover, R is free and unifies a large community of analysts and programmers. Currently, knowledge of R software and language is one of the most sought-after skills in the labour market. Now SSE Riga students learn R both theoretically and in practice ‒ applying their knowledge to real data in preparation for applying R skills in their future workplaces.

R programming is not delivered as a separate course but integrated into the SSE Riga BSc programme curriculum throughout all three study years – currently it is applied in nine courses, in particular in Mathematics, Statistics, Econometrics, Market Research, Financial Economics, and Artificial Intelligence. The same R skills are also required during the Bachelor Thesis writing process. The number of SSE Riga courses using R applications will only grow in future.

SSE Riga is one of the few business schools in the region that offers R programming integrated into its core courses. Undoubtedly, knowledge of R programming skills will increase the value of SSE Riga graduates in the international labour market.

SSE Riga Associate Professor Konstantins Benkovskis answers a few questions about R programming:


What is R programming used for?

R is a universal and highly efficient language for data analysis. It can be applied to virtually any problem in machine learning and quantitative data analysis, including dataset organization, creation of statistical models, predictions, or graphic representation of data.


What skills are needed for getting started?

Since we start from the very basics of R, no specific prior requirements are set for students. You can start and quickly proceed to a rather sophisticated level of data analysis even without any previous experience in programming. A good knowledge of mathematics and logic is an asset, of course.


How is R programming integrated into the BSc programme curriculum?

Learning a programming language is very similar to learning a foreign language – you need practice on a daily basis. This is why SSE Riga does not have one special course devoted to R, but rather integrates R into multiple courses at different stages of the BSc curriculum. The very first time students see R is in Year 1 Mathematics. At this stage, basic concepts such as variables, vectors, loops, and algebraic operations are introduced to students. In addition, practical assignments ease their understanding of how a variety of mathematical problems ‒ such as derivatives or constraint optimization ‒ can be solved numerically in practice. Since SSE Riga is a business school, the main application of R is data analysis, which is introduced during the Year 1 Statistics course. Students learn how to organize, analyse and visualise data, applying their theoretical knowledge of statistics to real datasets. These skills are also sharpened during the Year 1 Macroeconomics course.

Much more advanced data analysis methods and R functions are introduced to students during the Year 2 course in Econometrics and Market Research. Students who manage to pass these courses can proudly claim that they know quite a lot about machine learning on both theoretical and practical levels using R. These skills are applied later to financial and international trade data during the Financial Economics and International Economics courses in the spring semester of Year 2.

The course on Artificial Intelligence in Year 3 helps students to implement different machine learning and artificial intelligence approaches in their future business. Finally, most students will apply their, already advanced knowledge of R while writing their Bachelor Thesis.


What does a common R programming assignment look like (a sample from the study process)?

Perhaps you have already experienced a loan-granting decision made by robot. You fill in an online form giving your age, income level, education, required loan size ‒ and the machine provides a recommendation immediately! This has nothing to do with magic. In fact, this is exactly one of the exercises that SSE Riga students face during the Econometrics course. Students are provided with a large (over 4 000 observations) anonymized dataset on individual bank clients that contains information on loan size, age, income and other individual personal characteristics. On top of that, the dataset contains information on loan status. Students learn how to create a statistical model that predicts the probability of successful repayment of a loan for each person. Moreover, students are taught how to write an R script that performs this task and makes the decision automatically for any new loan applicant.