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Tom Hengl: “Modern challanges of geospatial data science: the Open-Earth-Monitor project”

Ben Graeler: “AI Strategy for Earth System Data – KI:STE project”

Martin Schultz: “Machine learning for weather, air quality and climate”

Markus Konkol: “Open Reproducible Research – Concepts, challenges, and solutions”

Jakub Nowosad: “Geocomputation with R’s guide to reproducible spatial data analysis”

Edzer Pebesma: “R-spatial updates: sf, sftime, stars”

Christian Autermann: “GeoNode as Research Data Infrastructure”

Martijn Visser; Maarten Pronk: “JuliaGeo: a gentle introduction”

Martin Fleischmann: “Introduction to GeoPandas and its Python ecosystem”

Krzystof Dyba: “Benchmarking R and Python for spatial data processing”

Ben Graeler: “Extreme events session”

Leandro Parente: “Accessing and using data cubes: spatial overlay, visualization and modeling – Python tutorial”

Markus Abel: “Stochastic processes, analysis, examples (Python tutorial)”

Edzer Pebesma & Leandro Parente: “Geo-arrow and geo-parquet”

Ribana Roscher: “Explainable ML”

Patrick Schratz: “Introduction to mlr3 (R tutorial)” and Patrick Schratz & Leandro Parente: “Spatial modeling using mlr3 (R tutorial)”

Hanna Meyer: “ML in R: how to deal with extrapolation and overfitting problems”

Tim Appelhans: “Visualization cloud-optimized (large) datasets in R (R tutorial)”

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