Geospatial Data Science Course
This course equips you with practical skills in geospatial data science applied to urban mobility, focusing on data processing, analysis, visualization, and reporting using Python and scalable tools.

4 to 360 hours of flexible workload
certificate valid 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
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
Your lessons are perfect. I purchased the one-year package and finally have the opportunity to follow various topics of my interest without needing to change platforms... I thank you for everything you do, I've already recommended you to other people...

Giulio CarloDigital Marketing Student
I like how the lessons are straight to the point and how I can switch chapters and skip content I don't need.

Mariana FerresPhotography Student
I like the content and the way videos are presented and transcribed, which speeds up the process!

Luciana AlvarengaNail Design Student
The platform is fast, simple to use. The diversity of content and complementary videos really help with learning.

André FelipePrompt Engineering Student
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