Python Foundation for Spatial Analysis

This class covers Python from the very basics. Suitable for GIS practitioners with no programming background or python knowledge. The course will introduce participants to basic programming concepts, libraries for working with spatial data, geospatial APIs and techniques for building spatial data processing pipelines.

Learning the basics of programming has become essential for geospatial professions. This class builds a strong foundation and gives you the resources to become a proficient programmer and leverage AI-coding tools. If you have struggled to get into programming on your own, this instructor-led class will help you overcome the hurdles and build your first project in Python.

Level: Beginner
Duration: 12 hours4 sessions of 3 hours each over 2 weeks
Prerequisites: Familiarity with spatial data and basic GIS concepts.

Ways to take this course

Every course is free to study on your own. The live classes add certification, support and a cohort to work through it with.

Self study

Free, at your own pace

Pre-recorded videos
Full course material

Free

Start learning

Live classes

Cohort-based, with certification

Live instructor-led Zoom sessions
Certificate of completion
Lifetime technical support
Mentoring

Next class: Oct 21–29, 2026

US$149 · ₹10500

Learning outcomes

Knowledge of how to setup the Python environment and install packages.
Ability to read and write spatial data, query web APIs, use geospatial packages and carry out basic geoprocessing tasks.
Familiarity with data science libraries to scale your analysis to large datasets.

Course outline

Session 1

Python Basics
- Introduction and Course Overview
- Variables
- Data Structures
- String Operations
- Loops and Conditionals
- Functions
Session 2

Data Processing
- Understanding Coordinate Systems
- Python Standard Library and 3rd Party Library
- Using Web APIS
- Reading/Writing Files
Assignment
Geocode Addresses with GeoPy
Session 3

Tabular and Vector Data
- Introduction to Pandas and GeoPandas
- Tabular Data Analysis with Pandas
- Vector Data Analysis with GeoPandas
Session 4

Raster Data and Scripting
- Introduction to Numpy and rioxarray
- Raster Data Analysis with rioxarray
- Building Scripts and Automating Workflows
After the course

Class Project
- Each participant will work on a project of their choice to complete within 2 weeks of the class. The topic can be selected by the participant or will be assigned by instructor based on their interest areas.
- 1-1 mentoring and email support will be available during the project.
- See Example Projects completed by previous participants to get an idea of what you can achieve after taking this course.
- Participants must complete the project to receive a completion certificate.

Certification

Upon successful completion of all the live online sessions, assignments and a class project, participants will be issued an employer-verifiable certificate from Spatial Thoughts. Learn more.

What participants say

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Even more than the nice, friendly class format that Ujaval and Vigna always run, the really cool thing is how the class is current with the relevant, current best practices. For instance, in this class session, what was so nice to learn was the approach to use AI tools in Python programming in a useful, careful, and appropriate way.

Nitin Pandit
Mentor

India Python Foundation for Spatial Analysis

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This is the second course I have taken with Spatial Thoughts and I am once again highly satisfied with Ujaval’s expertise and teaching style to learn complex topics. He is great at focusing on the critical building blocks to help his students independently create products by the end of the course.

Zach Torres
World Vision

United States of America Python Foundation for Spatial Analysis

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The Python Foundation for Spatial Analysis course by Spatial Thoughts was a highly valuable and practical learning experience. Prior to the training, I had little to no knowledge of Python, but the course provided a clear and well-structured introduction that helped me build a solid foundation.

I particularly appreciated the hands-on approach and the small class size, which made the learning environment more engaging and allowed for better interaction and understanding. Ujaval is a wonderful tutor, and the guidance provided throughout the course was both supportive and effective.

I am grateful for the opportunity to participate in this training, and I highly recommend it to anyone looking to develop practical skills in geospatial analysis using Python.

Vivian Ndidiamaka Asogwa
Lecturer, Department of Surveying and Geoinformatics, Federal Polytechnic Nekede, Owerri Imo State

Nigeria Python Foundation for Spatial Analysis

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I recently took the Python Foundations for Spatial Analysis course with Ujaval and Vigna. They created a supportive and engaging learning atmosphere which I really appreciated since this helped me focus on the class topics I was intimidated by.

During the class we covered APIs which I had been especially hesitant to dive into, but through the various exercises I became more comfortable and even ended up using two different APIs as part of my final class project. Grateful for Ujaval’s and Vigna’s encouragement! This class has boosted my confidence and I’m excited to keep trying new things.

Grecia White
Program Manager, Massachusetts Clean Energy Center

United States Python Foundation for Spatial Analysis

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An absolutely brilliant introduction to Python for spatial analysis! The course content is comprehensive and perfectly paced for beginners. I feel much more confident in my ability to use Python for my GIS work now. Thank you, Spatial Thoughts Team, for creating such a great resource!