Intermediate R –Data Science and Visualization Techniques Beyond Base R

Third-cycle level | 3.0 credits (HEC) | Course code: H7F6003
HT 2025
Study period: 2025-11-24 - 2025-12-05
LANGUAGE OF INSTRUCTION: The course is given in English
Application period: 2025-04-15 - 2025-05-06
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VT 2026
Study period: 2026-04-20 - 2026-05-01
LANGUAGE OF INSTRUCTION: The course is given in English
Application period: 2025-10-15 - 2025-11-05
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Course description

The intermediate R course covers more complex topics and builds upon the foundation established in basic R courses.

The course contains:

Recommended coding conventions and best coding practices
Functional programming, including advanced techniques for writing functions in R, such as closures, anonymous functions, and higher-order functions.
Object-Oriented Programming: An introduction to the basics of object-oriented programming in R, including classes, objects, and inheritance.
Advanced data manipulation, including topics such as regular expressions, string manipulation, and the use of the tidyverse packages for data cleaning and manipulation.
Advanced data visualization, including the use of advanced visualization techniques, such as interactive visualizations using shiny, and visualizing complex data using the ggplot2 package.
An introduction to machine learning using tensorflow and keras.

The course will also emphasize the use of best practices for reproducibility and collaboration. Introducing the concepts of writing modular and reusable code, using version control with Git, and using R Markdown for reproducible reporting.

Prerequisites and Selection

Prerequisite courses, or equivalent

Knowledge and/or skills in basic R, equivalent to course "H1F5300: Get started with R – Programming Basics, Data Analysis and Visualisation", "H5F2953: Statistics with R - from Data to Publication Figure" or corresponding courses. 

Selection

Selection will be based on:  

1) the relevance of the course syllabus for the applicant’s individual study plan/research (according to written motivation). 

2) start date of doctoral studies (priority given to earlier start date). 

3) Experience and education in R

Only applicants with a KI login (KI ID) can apply for this course during the course catalogue's regular application period. Applications for any remaining places may later be opened to other applicants.

Course director

Billy Langlet

Course syllabus

H7F6003

Department

Department of Medicine, Huddinge

Doctoral programme

**Not within a doctoral programme

Type of course

Statistics Software

Keywords

programming, R, RStudio, RMarkdown, intermediate, programmering

CONTACTBilly Langlet

billy.langlet@ki.se