Introduction to Data Analytics in R
Netherlands, Maastricht
| Study location | Online |
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| Type | Online Summer Courses, distance learning |
| Nominal duration | 1-week (2 ECTS) |
| Study language | English |
| Course code | MSS-SBE2001 |
| Tuition fee | €499 one-time |
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| Entry qualification | Enrolled as an Undergraduate student or Undergraduate diploma ▪ Knowledge of algebra (high-school level) The entry qualification documents are accepted in the following languages: English. Often you can get a suitable transcript from your school. If this is not the case, you will need official translations along with verified copies of the original. |
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| Language requirements | English The language of the course is English, so we expect a fluent level and the ability to follow and participate in class. |
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| More information |
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Overview
Please note that this course will take place online.
Course Description
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.
Goals
▪ 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.
Recommended Literature
The course is entirely self-contained but will make use of the statistical programming environment R:
▪ www.r-project.org
▪ www.rstudio.com
Teaching Methods
▪ Assignments ▪ Lectures ▪ Presentations ▪ Skills ▪ Work in subgroups
Assessment Methods
▪ Assignment ▪ Attendance
Course Coordinator
Dr. B. Foubert
Bram Foubert is Associate Professor at the Department of Marketing and Supply Chain Management at Maastricht University School of Business and Economics (SBE), where he teaches courses in data analytics and econometrics. His research interests are in the areas of consumer response modelling and retailing. More specifically, he investigates how marketing instruments, such as sales promotion, store environment, or advertising, affect purchase and consumption behaviour and customer life time. His research has appeared in the Journal of Marketing, Journal of Marketing Research, Journal of Retailing, and Marketing Science, among others.