The School covers key aspects of Applied AI, focusing on designing, developing, and deploying practical solutions to real-world problems. It aims to equip scientists, primarily from developing countries, to tackle local challenges and contribute to global sustainability goals.

Embedded devices running ML models are becoming increasingly powerful, evolving from Cloud-based AI to EdgeAI. This shift enables the creation of more complex, sustainable, and real-time AI solutions for applications such as environmental monitoring, particle detection and classification, radiation monitoring, smart agriculture, waste management, and beyond.

The School includes hands-on exercises, group discussions, and case studies to reinforce key concepts. Participants will be introduced to open-source methods, software tools, and hardware platforms relevant to real-world deployment.

The School is linked to multiple MSCA EU-funded projects (ROBUST / AIAS / ANTIDOTE), and the Annual Workshop of the the  the Rural Environmental Monitoring via ultra wide-ARea networKs And distriButed federated LEarning (REMARKABLE) EU project.

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Grants: A limited number of grants are available to support the attendance of selected participants, with priority given to participants from developing countries. There is no registration fee.