[UNDRR Masterclass series] AI for Multi-Hazard Early Warning Systems: A Hands-On Guide to Strengthening Early Warning and Response
- English
Capacity for live online sessions is limited to 1,000 participants on a first-come first-served basis
Date and Time
Date: 16, 23, 30 September 2026
Time: 12:00 - 13:30 Geneva Time (CET)
Background
Following the successful AI Masterclass Webinar in late 2025 which attracted more than 1,000 participants, and In support of the Early Warnings for All (EW4All) initiative, UNDRR and Google propose a joint AI Masterclass Webinar Series. This hands-on, technically rigorous series is designed to bridge the gap between cutting-edge Artificial Intelligence (AI) research and practical, on-the-ground disaster risk reduction. Over three targeted sessions, participants will explore how Google’s Climate, Earth and Crisis Resilience AI can help governments and humanitarians strengthen Early Warning Systems and Anticipatory Action.
The masterclasses are designed to:
- Build foundational understanding of AI for climate and crisis resilience: Demystify AI and explore how machine learning can support flood modelling, weather and cyclone forecasting, and geospatial analysis.
- Develop practical skills and provide operational tools: Equip governments and humanitarian organizations with actionable knowledge and ready-to-use tools to strengthen and complement Early Warning Systems and Anticipatory Action programmes.
- Showcase real-world impact: Demonstrate how partners use AI-enabled tools to trigger early action, target interventions, and conduct rapid damage assessments when disasters strike.
Programme
Session 1 (16 Sep, 12:00 - 13:30 CEST, 90 minutes): Preparing for El Nino: AI-driven Flood Predictions
Session 2 (23 Sep, 12:00 - 13:00 CEST, 60 minutes): Revolutionizing Weather Predictions with AI
Session 3 (30 Sep, 12:00 - 13:00 CEST, 60 minutes): Leveraging AI in Earth Science for Impact Assessment
Certificate:
Certificate of Completion will be provided to masterclass participants who attend all three (3) masterclass sessions.
Attendance will be tracked via Zoom registration and participation logs.
** Capacity for live online sessions is limited to 1,000 participants on a first-come first-served basis.