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SUMMARY:Online course: ML for Earth Systems Modelling - Architectures\, da
 ta\, and prediction
DTSTART:20260601T070000Z
DTEND:20260724T144500Z
DTSTAMP:20260527T013800Z
UID:indico-event-535@events.ecmwf.int
CONTACT:training@ecmwf.int
DESCRIPTION:\nThis online course explores the technical foundations of mac
 hine learning (ML) for weather and climate prediction within the Destinati
 on Earth (DestinE) initiative. As the second course in ECMWF’s three-cou
 rse ML learning pathway\, it focuses on how modern AI forecasting systems 
 are designed\, trained\, and evaluated using real-world Earth system data 
 and workflows.\nParticipants will gain insight into the architectures\, da
 tasets\, infrastructure\, and evaluation methods that underpin data-driven
  weather prediction systems. The course combines conceptual explanations w
 ith practical examples relevant to operational forecasting and the develop
 ment of next-generation Earth digital twins.\nThe training provides a stru
 ctured pathway from data handling and preprocessing to advanced AI forecas
 ting workflows\, uncertainty quantification\, and benchmarking approaches 
 used in contemporary Earth Systems modelling.\nMain topics\nThe course wil
 l cover the following themes:\n\nFoundations of ML for weather prediction\
 nDeep learning architectures for atmospheric dynamics\nDatasets\, data han
 dling\, and preprocessing workflows\nCompute infrastructure and distribute
 d systems for ML forecasting\nAI forecasting systems (AIFS and AIFS-ENS) a
 nd operational workflows\nUncertainty quantification and probabilistic pre
 diction\nEvaluation frameworks and benchmarking methods\nThe Anemoi framew
 ork for data-driven weather forecasting\n\nTarget audience\nThis course is
  part of a series designed for:\n\nResearchers and practitioners in meteor
 ology and climate science\nTechnical specialists from meteorological servi
 ces and climate centres\nAcademic and industry professionals working with 
 Earth Systems data and AI workflows\n\nThis second course\, Architectures\
 , Data\, and Prediction\, specifically targets technical learners with exp
 erience in Earth system sciences or related disciplines who want to deepen
  their understanding of machine learning workflows for weather prediction 
 and forecasting systems.\nRequirements\nParticipants are expected to have:
 \n\nA background in meteorology\, climate science\, Earth Systems Sciences
 \, or related fields\nBasic programming experience (preferably Python)\nFa
 miliarity with statistics and introductory machine learning concepts\nExpe
 rience interpreting geophysical datasets and Earth system data workflows\n
 \nPrior completion of the first course in this series\, Foundations and Ne
 w Frontiers is recommended\, but not required.\nRegister now!\nRegister fo
 r this course through our eLearning portal.\n\nhttps://events.ecmwf.int/ev
 ent/535/
IMAGE;VALUE=URI:https://events.ecmwf.int/event/535/logo-1447777313.png
LOCATION:Online
URL:https://events.ecmwf.int/event/535/
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