Geospatial Data Science Course
This course equips you with practical skills in geospatial data science tailored to urban mobility challenges. Through hands-on projects, you'll learn to process and analyze large-scale trip data using Python's geospatial libraries, build insightful visualizations like flow maps and OD matrices, and develop scalable workflows for cloud environments. By the end, you'll be able to deliver stakeholder-ready reports that transform raw mobility data into strategic insights for better urban planning.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Master geospatial data science for urban mobility in this concise, hands-on course. Learn to clean and validate large trip datasets, run exploratory analyses, build spatial joins, OD matrices, grids, and flow maps, and create clear visualisations with Python tools. You also practise scalable workflows, cloud-ready pipelines, and stakeholder-focused reports that turn complex mobility data into actionable, well-documented insights.
Elevify advantages
Develop skills
- Urban mobility EDA: quickly profile trips, peaks, and modal splits for cities.
- Geospatial Python stack: use GeoPandas, Shapely, and Rasterio for fast analysis.
- OD flow modelling: build and map origin–destination flows to reveal transport gaps.
- Scalable pipelines: process big mobility data with Spark, Dask, and cloud storage.
- Stakeholder reporting: turn complex maps and metrics into clear, actionable briefs.
Suggested summary
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