Syllabus
Basic course information and syllabus at: https://docs.google.com/document/d/1YdLzcs8L-_NV9nyGq-9VulAS_uojRAnMN37l7JSDRN8/ (faculty account needed)
The primary form of common communication is Google Classroom. This virtual platform will be used for sharing the course materials and homework assignments.
Annotation
The objective of the course is to provide students with basic principles of using R and Python programming languages in geosciences. Students will learn and practise the most common principles of data assessment typical for geoscience applications based on selected exercises, such as working with large data sets (time series, spatial data), its basic statistical evaluation (correlation, regression, trends in time series, interpolation) and visualisation. The course is focused on
1) assessment and statistical analysis of hydrological and climatological data,
2) modelling selected hydrological processes,
3) linear models,
4) methods of quantification of spatial autocorrelation,
5) principal component analysis, and
5) using of Python in remote sensing. A part of the course will also be a “coding club”, which enables students to discuss with lecturers their data and codes used for their final theses. The course is intended mainly for master students of Physical geography and geoecology, Hydrology and hydrogeology, as well as for bachelor students of Physical geography and geoinformatics and Geography and Cartography.