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 |
| Course code | MSS2010 |
| Tuition fee | €599 one-time |
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| Entry qualification | Enrolled as an undergraduate student or holder of an undergraduate diploma, including those pursuing advanced studies or professional careers. ▪ 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 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.
Goals
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.
Recommended Literature
• Course manual (available from the Syllabus tab on Canvas);
• Lecture slides, available from Canvas;
• Assignments and datasets, available from Canvas;
• Background material;
• An Introduction to R available from cran.r-project.org/ (optional)
_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
Lectures, Interactive Class, PBL Tutorials
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
Central European Time
Central European Time