Ready to unlock the power of machine learning for geospatial analysis?

Join us for Week 4: Machine Learning in Google Earth Engine. This week, we explore how to train, test, and apply machine learning models directly within Google Earth Engine to extract meaningful insights from satellite data.

You will learn how Earth Engine enables large-scale geospatial machine learning for land cover classification, environmental monitoring, and spatial prediction.

What’s on the Agenda?

• Machine Learning Basics in GEE: Understanding supervised classification workflows.

• Training Data Preparation: Creating and managing training samples from FeatureCollections.

• Model Training: Applying classifiers such as Random Forest in Google Earth Engine.

• Accuracy Assessment: Evaluating classification performance and improving model results.

• Visualization: Displaying classified outputs and interpreting spatial patterns.

🛠 Prerequisites:

A basic understanding of the GEE Code Editor.

Familiarity with JavaScript/Python variables.

An active Google Earth Engine account.

📅 When & Where
Date: 14 March 2026
Time: 8:00 PM EAT
Location: Virtual

👉 Don’t miss this opportunity to learn how AI and machine learning can transform geospatial analysis. Register now and secure your spot!