Course curriculum
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1
Module 1 - Earth Observation & the Geospatial domain
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Earth Observation introduction, principles & applications
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Earth Observation physics & image characteristics
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Earth Observation platforms & sensors
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Some questions to review
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2
Module 2 - Machine / Deep Learning Concepts
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Machine Learning Concepts
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Terminology quiz
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Some questions to review
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3
Module 3 - Diving into the Picterra platform - Imagery, and Account Basics
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Setup Tasks
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Diving into the Picterra platform - Imagery and Account Basics
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One more thing!
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4
Module 4 - Training your first detector
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Training your first detector
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5
Module 5 - Running your detector and managing results
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Running your detector & managing results
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Building Detector Exercise
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Building Detector Solution
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Sheep Detector Exercise
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Sheep Detector Solution
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6
Module 6 - Advanced features & Next Developments
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Advanced Features & Next Developments
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Road Cracks Detector Exercise
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Road Cracks Detector Solution
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Solar Panels Detector Exercise
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Solar Panels Detector Solution
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7
Module 7 - Picterra API & python library
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Setup tasks
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Picterra API & Python Library
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8
Module 8 - 3rd party tools (QGIS and Tableau)
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Setup Tasks
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3rd Party Tools (QGIS & Tableau)
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9
Module 9 - Case studies
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Case studies
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10
Module 10 - Now it's your turn!
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Use case brainstorming!
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Course Survey
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Instructor(s)

CTO
Frank De Morsier

Computer Vision Scientist
Roger Fong

Lead Software & ML Engineer
Julien Rebetez