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Lillie Academy · Course contents

Sixteen core modules, plus optional electives, beginner to professional

The full remote-sensing machine-learning curriculum: cloud-native geospatial data, optical and SAR analytics, forestry and biomass, deep learning and foundation models, and production systems. Phase 0 is a free preview.

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Phase 0 · Foundations

0.1 Your Geospatial Python ToolkitFree preview0.2 How Earth Observation WorksFree preview0.3 Geospatial Data 101Free preview0.4 Git and GitHubFree preview

Phase I · Data, physics, radar

1 The Cloud-Native Geospatial StackFull program2 Optical Radiometry and Burn SeverityFull program3 SAR Fundamentals IFull program

Phase II · Core analytics

4 Classical ML for EOFull program5 Forestry, Lidar, and BiomassFull program6 SAR Fundamentals II: Time Series and ChangeFull program

Phase III · Deep learning

7 Segmentation NetworksFull program8 Geospatial Foundation ModelsFull program9 SAR Deep Learning, InSAR, and NISARFull program

Phase III · Electives (optional)

9.5 Solid Earth, Deformation, and GeohazardsOptional elective9.6 Resources, Minerals, and EnergyOptional elective9.7 Agriculture and Food SecurityOptional elective

Phase IV · Production and job

10 Wildfire Systems End to EndFull program11 MLOps and Cloud DeploymentFull program12 Portfolio, Interviews, ApplicationsFull program