PyEarthtools Training under EW4Energy Project in Ghana

🌍 Can Artificial Intelligence transform weather forecasting and climate research in Africa? In this training session under the EW4Energy Project in Ghana, participants are introduced to PyEarthTools—an innovative open-source framework designed to simplify environmental data science and machine learning workflows for weather and climate applications. From handling complex Earth observation datasets to building AI models for forecasting, the session demonstrates how modern AI tools can accelerate research and operational decision-making. The training is facilitated by Stephen Haddad of the UK Met Office, who shares the vision behind PyEarthTools and explains how it supports reproducible science, efficient data processing, and collaborative AI development for environmental applications. Through practical demonstrations using real-world datasets, viewers gain valuable insights into the future of AI-powered weather and climate intelligence. Whether you're a researcher, student, data scientist, or weather enthusiast, this video offers practical knowledge and inspiration for applying AI to some of the world's most pressing environmental challenges. Here are links that Stephen shared during the meeting, and also a link to the slides: Slides: https://docs.google.com/presentation/d/1C8... PyEarthTools Docs: https://github.com/ACCESS-Community-Hub/Py... PyEarthTools repo: https://github.com/ACCESS-Community-Hub/Py... JASMIN site archive repo: https://github.com/MetOffice/pyearthtools_... AI Data Readiness material: https://github.com/MetOffice/ai_data_readi... A reminder that if you'd like to get support with PyEarthTools, there is a monthly user forum. 💬 What environmental problem do you think AI can help solve in Africa? Let us know in the comments! 👍 Like | 🔔 Subscribe | 📤 Share to support more content on AI, weather, climate, and environmental science.