Data science using R
📑 The course in brief
Focus: You will be introduced to the statistical programming language R and acquire practical knowledge about the fundamental tools of data science and machine learning.
How: The course comprises a mixture of (i) lectures, in which I introduce concepts in the classroom, (ii) automated hands-on exercises for you to do at home on your own and (iii) flipped-classroom elements where you watch videos at home and we practice the content together in class.
Prerequisites: The course does not require you to have any prior knowledge in R or any other programming language. Depending on your prior knowledge or affinity to programming, the course will be quite demanding, but equip you with computational skills that are most valuable both within academia and the business world.
🎯 Learning Objectives
- Use R together with the integrated development environment R Studio
- Understand the use of R packages to perform specific data analytic tasks
- Write reproducible data analysis reports using Quarto
- Transform raw data into tidy data, which is suitable for further analysis
- Choose and justify the correct visualization approach, and create appealing visualizations using the R package
ggplot2 - Implement and interpret linear regression models with numerical and categorial variables
Historic versions of the course