GIS with Python for Developers

In this course, you will learn how to work effectively with geospatial data using Python. Over two practical days, you will explore the fundamentals of GIS, learn how to analyze vector and raster data, work with public geodata sources, and create compelling visualizations using modern Python tools. By combining hands-on exercises with real-world examples, you will gain the skills needed to build geospatial analyses and interactive maps for professional applications.

What you will learn

Day 1

• Introduction to GIS and Geodata: What GIS is, how geographic data works, and how Python fits into a modern geospatial workflow.

• Map Projections & Coordinates: Understanding key projection systems such as RD (Rijksdriehoekstelsel) and WGS84, and applying them correctly in your analyses.

• Visualization with GeoPandas & Plotly Express: Creating your first geospatial plots and transforming raw geodata into clear visual insights.

Day 2

• Spatial Analysis: Performing point-in-polygon operations, spatial joins and other analyses used in location-based decision-making.

• Working with Public Geodata: Using open datasets such as PDOK and the Dutch Cadastre to enrich and visualize your projects.

• QGIS for Advanced Visualizations: Building interactive and sharable maps and using QGIS for deeper geospatial analysis.

After this course, you will be able to:

• Independently load, manipulate and analyze geospatial datasets using Python.

• Apply projections and coordinate systems correctly in your workflows.

• Perform spatial analyses for real-world use cases.

• Create interactive and shareable geospatial visualizations.

• Combine Python and QGIS effectively for advanced GIS applications.

Who this course is for

• Data scientists, analysts and developers who want to work with geospatial data in Python.

• Teams and organizations that use geodata for decision-making, urban planning, marketing or policy analysis.

• Anyone — beginner to advanced — looking to apply Python in GIS-driven projects.

Prerequisites

• Basic Python knowledge.

• General understanding of data analysis is helpful.

• No prior GIS experience required.

Course content 

Part 1

• GIS fundamentals & geodata concepts.

• Projections and coordinate reference systems.

Part 2

• Your first geospatial workflows in Python.

• Visualization with GeoPandas and Plotly Express.

Part 3

• Spatial analysis techniques.

• Spatial joins, geometry operations, and point-in-polygon.

Part 4

• Working with public datasets.

• PDOK, Dutch Cadastre, and other open data sources.

Part 5

• Visualization & mapping.

• Interactive maps and advanced visualizations with QGIS.

Part 6

• Best practices & Q&A.