Length of study
50 hours
Type of Programme
Microcertificate programmes
Form
Language
English
Fee
7500 CZK
Application deadline
31/8/2025
Annotation
Standalone course validated by the micro-credential (paid course) 1. Introduction to Python for Data Science 2. Open Data Science, Data manipulation in Python (pandas) 3. Spatial data (geopandas) 4. Spatial relationships (libpysal) 5. Exploratory spatial data analysis (esda) 6. Point patterns (pointpats) 7. Clustering (scikit-learn) 8. Raster data (xarray) 9. Interpolation (tobler, pyinterpolate) 10. Regression (statsmodels, mgwr)
Location
online (link bude zaslán všem přihlášeným / online, the link will be sent to all registered users
Results of learning
After finishing the course, students will be able to: • Describe advanced concepts of spatial data science and use the open tools to load and analyze spatial data. • Explain the motivation and inner logic of the main methodological approaches of open SDS. • Critically evaluate the suitability of a specific technique, what it can offer, and how it can help answer questions of interest. • Apply several spatial analysis techniques and explain how to interpret the results in the process of turning data into information. • Work independently using SDS tools to extract valuable insight when faced with a new dataset.