Course

Course Overview

This comprehensive 20-day course is designed to equip participants with the skills required to master Google Earth Engine (GEE). From basic operations to advanced geospatial analysis, participants will gain hands-on experience in remote sensing, land use change detection, vegetation indices, and machine learning applications. The course covers vector and raster data processing, GIS-based spatial analysis, time-series trend analysis, supervised and unsupervised classification, and multiple index calculations. Whether you are a beginner or an advanced user, this course will provide step-by-step guidance on using GEE for real-world applications.

Why Enroll in This Course?

Expert-Led Training – Learn from experienced remote sensing and GEE professionals.
Practical Hands-On Learning – Work with real-world datasets and case studies.
Advanced Data Processing Techniques – Implement classification models, change detection, and time-series analysis.
Comprehensive Learning Materials – Access study guides, downloadable scripts, and recorded sessions.
Live Project Implementation – Apply concepts to environmental and agricultural monitoring projects.

Who Should Take This Course?

Students & Researchers – Build expertise in remote sensing and geospatial analysis.
GIS & Remote Sensing Professionals – Enhance career prospects with GEE-based data analysis.
Environmental Scientists & Land Managers – Learn to analyze land cover and environmental changes.
Data Scientists & ML Engineers – Integrate machine learning with remote sensing data.

Course Features

Live & Recorded Classes – Access interactive sessions and lifetime recorded content.
Comprehensive Study Materials – PDFs, PPTs, and coding scripts for every module.
Hands-On Experience – Apply GEE for real-world geospatial analysis.
Multi-Device Access – Learn seamlessly on mobile, laptop, or PC.
Capstone Project – Work on a real-world GEE-based geospatial project.

Course Outcomes

By the end of this course, you will be able to:

Process and analyze satellite imagery using GEE’s cloud computing platform.
Perform supervised & unsupervised classifications (SVM, Random Forest, K-means).
Calculate and interpret multiple vegetation indices for environmental monitoring.
Conduct time-series and trend analysis for change detection.
Automate geospatial workflows using JavaScript and Python in GEE.

Enroll Now and take your Google Earth Engine skills to the next level!