Geospatial Data Science Course
This course equips you with geospatial data science skills for urban mobility. Utilise Python tools for mapping, big data processing, and reproducible workflows to convert raw trip data into insightful visuals and practical recommendations for technology and city planning projects. Ideal for hands-on learning in real-world applications.

flexible workload of 4 to 360h
valid certificate in your country
What will I learn?
Gain expertise in geospatial data science focused on urban mobility through this practical course. You will learn to clean and validate large trip datasets, perform exploratory analyses, create spatial joins, origin-destination matrices, grids, and flow maps, and develop effective visualisations using Python libraries. Additionally, master scalable workflows, cloud-based pipelines, and stakeholder reports that transform complex mobility data into actionable and well-documented insights.
Elevify advantages
Develop skills
- Conduct urban mobility exploratory data analysis to profile trips, peak hours, and modal splits efficiently.
- Leverage the geospatial Python stack including GeoPandas, Shapely, and Rasterio for rapid spatial analysis.
- Model and visualise origin-destination flows to identify transportation gaps in cities.
- Build scalable data pipelines using Spark, Dask, and cloud storage for large mobility datasets.
- Create stakeholder-focused reports that simplify complex maps and metrics into actionable summaries.
Suggested summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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