Python Foundation for Spatial Analysis – June 2025 Cohort

This cohort is now full. You may sign-up to be notified when the next cohort is scheduled.

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

Learning programming takes a lot of practice and months of continuous learning. This class is intended to jump-start your journey by building a foundation and giving you the resources to become a proficient programmer. Each class is limited to a small batch to ensure individual attention, support, and mentoring are given to each participant.

Session 1: Getting familiar with Python

  • Setting up the environment using Anaconda and Jupyter notebooks
  • Programming basics – variables, data structures, functions, flow control
  • Installing and using packages (geopy)

Session 2: Working with Web APIs and Files

  • Using web APIs (openrouteservice)
  • Reading and writing files (file I/O, csv)

Session 3: Spatial Analysis 

  • Introduction to data science workflows (pandas)
  • Spatial analysis with Vector data (geopandas)

Session 4: Raster Data Processing and Automation

  • Introduction to arrays (numpy)
  • Raster data processing (rasterio)
  • Building scripts and automating workflows

Class Project

  • Each participant will pick a project relevant to their interest to complete within 2 weeks of the class. 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.

This class does NOT cover data visualization libraries. We cover data visualization and building apps in our intermediate course Mapping and Data Visualization with Python.

Learn more about the course content, student reviews, and project expectations on the Course Homepage.

Cost

The course fees are USD $149 / INR ₹10500 + GST.

Student discounts available [Learn more]

Schedule

The course shall be held as a live online interactive class offered in 4 sessions of 3 hours each over two weeks. The classes will be conducted over Zoom.

Below is the schedule for live sessions. Please verify the local times before registering.

It is recommended to attend the sessions live for the optimal experience. We also record the live sessions and make them available to registered participants immediately after each day. If you do miss a session – you will be able to catch up using the recorded videos.

Register

Please use the appropriate forms below to book a seat. You must complete the online payment to confirm your spot. We accept all major credit/debit cards from over 150 countries. Indian residents have an option to pay via UPI also. We have a very liberal cancellation policy.

Registration for Non-Indian Residents

Registration for Indian Residents

A GST charge of 18% will be applied to the course fees upon checkout.

Course Reviews

I have taken various different courses for Python and GIS, free and paid. This course was excellent. It gave me exactly the information I needed to be a better programmer focused specifically on spatial analysis. Ujaval is a wonderful teacher. He is incredibly generous with his knowledge and an excellent communicator. I am so happy I found Spatial Thoughts.

Colby Smith, GIS Specialist, Tetra Tech, United States.

Spatial Thoughts is known for offering excellent courses, and their “Python Foundation for Spatial Analysis” course is no exception. This course likely provides a good foundation in Python programming specifically tailored for spatial analysis tasks. By taking this course, you can expect to learn key concepts and techniques, such as working with geospatial data structures, performing spatial operations, manipulating vector and raster data, and automating spatial workflows.

Younes Abid, Ph.D Senior Data scientist NLP, CV, SAR, BAYANAT-UAE.

My current PhD work involves analysis of large geospatial datasets. With this course, I am able to automate my work using python which can save my time. The course content is vast enough to cover most of the aspects. The best part of the course is lifetime support which can help in future if at any point we get stuck. Another good thing about course is the requirement of project. This can help us revise the concepts just after the course. Looking forward to more of the courses.

Shamaila Fatima, Indian Institute of Technology Bombay, India