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Spaceborne AI for Earth Observation and Remote Analytics Training
"Spaceborne AI for Earth Observation and Remote Analytics Training" focuses on deploying secure, onboard AI for satellite-based imaging and analytics. Participants learn how to ensure algorithmic integrity, prevent payload hijacking, and secure satellite-to-ground inference results. Cybersecurity is central to maintaining trusted analytics pipelines that support disaster response, defense monitoring, and national intelligence operations.
Course Overview
None
Learning Objectives
- Understand the principles of applying AI for Earth observation and remote analytics from space.
- Learn about different AI algorithms used for analyzing spaceborne data.
- Explore the applications of spaceborne AI in various domains.
- Consider the computational and resource constraints of AI in space.
- Securing the AI algorithms and data processing pipelines used in spaceborne systems is vital for preventing manipulation of critical Earth observation data.
Framework Connections
The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):
Competency Areas
Feedback
If you would like to provide feedback on this course, please e-mail the NICCS team at NICCS@mail.cisa.dhs.gov. Please keep in mind that NICCS does not own this course or accept payment for course entry. If you have questions related to the details of this course, such as cost, prerequisites, how to register, etc., please contact the course training provider directly. You can find course training provider contact information by following the link that says “Visit course page for more information...” on this page.