R Programming
This course gives you tools for a professional statistician to work with data analysis, machine learning and applications in artificial intelligence. In the course, you will learn, among other things, to write and organize R programs, to perform statistical calculations and simulations using R packages, and to improve R program code.
Statistical programming skills are required when working with data analysis, machine learning and with AI applications. R is nowadays a standard tool for professional statisticians working in data science as well as for many researchers. This course gives you programming skills in the programming language R.
In this course you will learn basic programming concepts such as data structures, functions and objects, strings, conditional statements, iterations. You will also learn methods for code performance optimization and debugging and to develop your own R packages. The course also provides an introduction to object-oriented programming and parallel programming.
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Course structure
The course is given at day time, full time.
The course forms a part of the Master's Program in Statistics, but it can also be studied as a freestanding course.
Teaching format
The teaching forms consists of lectures and computer labs. The course is given in English.
Course Information
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Course description ht-24 (191 Kb)
More information for registered students will be found in Athena.
Assessment
Examination will be in the form of a written test and a written hand in assignment.
Examiner
Course coordinator
You will find Parfait's reception hours in the link above. If you want to visit Parfait outside of her reception hours, you are welcome to e-mail herfor an appointment.
Teacher
Also teaching the course is Ralf Xhaferi.
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Schedule
The schedule will be available no later than one month before the start of the course. We do not recommend print-outs as changes can occur. At the start of the course, your department will advise where you can find your schedule during the course. -
Course literature
Note that the course literature can be changed up to two months before the start of the course. -
Course reports
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Contact
If you have questions about the course, please contact the course coordinator:Parfait Munezero.
If you have questions about studying at the Department of Statistics, please contact our study- and career counselor.
