Introduction to Data Analytics in R
Netherlands, Maastricht
| Study location | Netherlands, Maastricht |
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| Type | Summer Courses, Full-time |
| Nominal duration | 1-week (2 ECTS) |
| Study language | English |
| 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
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) control flow 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, PBL
Assessment Methods
Assignment, Attendance
Course Coordinator
Dr. Bram Foubert
This course is also offered online and can be found here:
maastricht.dreamapply.com/courses/course/256-introduction-data-analytics-r—online