Environmental Data Science
Umweltdatenwissenschaft
6 CPWinterEN
Prerequisites
Recommended, as written
• Experience in R programming language • Basic knowledge of statistics (probability theory, hypothesis testing, correlation, linear model)
Contents
Part 1. Introduction to environmental data science Part 2. Data handling - Coding Basics in R, data import & data transformation Part 3. Data visualization - Various types of data visualization Part 4. Data analysis - Basic statistics - Statistical modelling: classification and regression - Machine learning modelling: Classification and regression Part 5. Data interpretation - Model interpretation - Common pitfalls Part 6. Data communication - Storytelling with data: Basic rules & practical tips
Learning outcomes
After the course, students will acquire both hard and soft data science skills essential for solving issues in environmental science, such as data handling, data visualization, data analysis, data interpretation, and data communication. These practical skills will be supported by fundamental statistical and programming knowledge. The students will be fluent in the R programming language beyond the basic level.
Assessment
• Exercises during course (10 small programming exercises; 6% each; 60% in total) • Oral presentation based on self-organized project: 15 min incl. discussion (40%)
Literature (7)
- H. Wickham & G. Grolemund: R for Data Science (https://r4ds.had.co.nz/index.html)
- R. A. Irizarry: Introduction to Data Science (https://rafalab.github.io/dsbook/)
- Hands-On Programming with R (https://rstudio-education.github.io/hopr/index.html)
- C.O.Wilke: Fundamentals of Data Visualization (https://clauswilke.com/dataviz/)
- B. Boehmke & B. Greenwell: Hands-On Machine Learning with R (https://bradleyboehmke.github.io/HOML/)
- C. Molnar: Interpretable Machine Learning (https://christophm.github.io/interpretable-ml-book/)
- C. N. Knaflic: Storytelling with Data (https://www.storytellingwithdata.com/)
Remarks
This module will be offered as a block course. Please bring your laptop.
Source: BTU's module description · retrieved 28 Sep 2026Original