Machine Learning and Deep Learning for Earth Observation

About this course

Greetings to Colleagues from Every Corner of the World!

Welcome to Essentials of Machine Learning and Deep Learning for Earth Observation - your gateway into the rapidly growing field of AI4EO. This course is designed to give scientists, engineers, researchers, and data enthusiasts a clear and practical foundation in the core ML and DL techniques driving innovation in Earth Observation, while also emphasizing real-world challenges and solutions.

Across three hours of focused content, you’ll move from the basics of machine learning pipelines and classic algorithms to modern deep learning architectures like convolutional, recurrent, and generative networks. You’ll discover how these methods power essential AI4EO applications such as scene classification, semantic segmentation, object detection, and change detection, and learn best practices for effectively preparing and handling geospatial data.

No advanced background is required - just basic Python skills and curiosity. Through concise explanations, Earth Observation examples, and hands-on coding exercises, you’ll build confidence in applying ML and DL to remote-sensing data.

By the end of this course, you’ll have the knowledge and skills to appreciate practical limitations, start building your own AI-powered geospatial solutions, and establish a solid foundation for exploring specialized AI4EO research and applications, including scene classification, semantic segmentation, object detection, and change detection.

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