Start your journey into geospatial data science and build skills used to analyze, visualize, and manage spatial data. This beginner-friendly program guides you from core GIS concepts to modern geospatial workflows using industry tools and technologies.
You’ll begin with spatial fundamentals, including coordinate systems, vector data, and Python-based geospatial analysis using GeoPandas. As you progress, you’ll learn desktop GIS with QGIS, automate workflows with PyQGIS, and work with spatial databases using PostGIS.
The program then introduces raster processing and remote sensing, where you’ll analyze satellite imagery using Rasterio and GDAL. You’ll also learn to design maps, build interactive web maps, and use cloud-based tools like Google Earth Engine.
In later courses, you’ll explore spatial analysis, 3D data using LiDAR, and machine learning techniques for geospatial data. Finally, you’ll work with cloud platforms, build ETL pipelines, process real-time data streams, and analyze climate datasets.
Applied Learning Project
Build real-world experience through guided, hands-on projects integrated across the program. You’ll complete projects in desktop GIS and spatial databases, remote sensing analysis, web mapping and visualization, and geospatial machine learning.
Each project focuses on applying the tools and techniques learned in the courses—such as QGIS, GeoPandas, PostGIS, Rasterio, GDAL, and Google Earth Engine—to solve practical spatial problems.
The program concludes with a capstone project in geospatial data engineering, where you’ll work with cloud platforms, automate ETL pipelines, process streaming geospatial data, and analyze climate-related datasets.
These projects help you build a portfolio that demonstrates your ability to work across the full geospatial data workflow.
