Available courses
Building foundational and practical capacity for African-led applications of artificial intelligence in weather forecasting, climate modelling and early warning services.
A hands-on course on organising, cleaning, processing and visualising climate datasets for operational climate services.
A course focused on producing, interpreting and communicating climate information for users in agriculture, water, disaster risk management and planning.
A practical course on daily forecast operations, including data monitoring, model interpretation, forecast briefings and warning preparation.
A 2026 on-the-job training programme supporting African institutions to strengthen practical skills in forecasting, climate services, data analysis and early warning operations through hands-on, workplace-oriented learning.
A course on short-range forecasting methods, radar and satellite interpretation, convective systems, heavy rainfall and early warning applications.
A hands-on course introducing operational weather forecasting, including weather analysis, model guidance, forecast verification and the use of forecasts to support preparedness and decision-making.
A hands-on course on analysing rainfall, temperature, drought and climate variability using Python, gridded datasets and station observations.
A course on seasonal prediction, forecast interpretation, regional climate outlooks and communication of uncertainty to climate-sensitive sectors.
An introductory course on climate monitoring and climate services, covering climate data sources, seasonal information, climate indicators and practical applications for decision-making and resilience planning.
AI for Climate Services is a one-week introductory course that provides practical foundations in Artificial Intelligence and Machine Learning for weather, climate, and early warning applications. Participants will learn basic AI concepts, explore climate data sources, understand simple machine learning workflows, and examine how AI can support forecasting, climate services, and impact-based decision-making.
A foundational course introducing artificial intelligence and machine learning concepts, with practical examples of how AI can support weather forecasting, climate services and data-driven decision-making.
A course on linking hazard forecasts with exposure, vulnerability and potential impacts to support more actionable early warnings.