Topic outline

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    Then select the course you are interested in, fill in the application form & submit it. You will be contacted as soon as the selection of candidates is completed. 

    For a comprehensive list of all our training, check out the calendar.

    How to apply for a short course

    Click here to apply for short courses on Data Discovery for Weather, Oceanography, Air Quality and Climate.

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  • Introduction to Machine Learning for Earth Observation - A practical approach 2024

    This online course is an introduction to Artificial Intelligence (AI), Machine Learning and Deep Learning applied to Earth observation data. The aim of the course is to provide an overview of machine learning potential for EUMETSAT data and the main machine learning techniques, with hands-on modules using real world data. The course is composed of different modules, addressing both theory and practical examples.

    The course will cover: 

    • The main branches of machine learning: Supervised and Unsupervised Learning
    • Deep Learning
    • Existing open source tools 
    • How to build AI workflows
    • Hands on: classification, regression, clustering and image classification tasks
    • Agents, bots and Large Language Models 

    Dates: 29, 30 April and 2 May 2024.

    The course hours will be from 10:00 to 16:30 CEST each day, with a longer break from 12:00 to 13:30.

    Deadline for applications: 18 April

    Target Audience

    Member State weather and associated services starting to work in AI/ML on weather data.
    The course is aimed at people with little prior knowledge. You will need to be comfortable to edit some python using Jupyter notebooks. 

    Expected outcomes
    At the end of the course you will be able to:

    • understand how to address your problem using machine learning techniques;
    • create your own workflow based on the templates provided in the course;
    • find tools from the various existing libraries;
    • appreciate the limitations of you knowledge and where to find expert knowledge. 

     How to apply

    If you already have an account on this platform, use the link below to submit your application form.
    Otherwise, please make sure you create an account: click on Login (on the top right section of the page), create a new user (Create an account), and follow the procedure. With your new account, please log in, then access the 'Apply for Courses' section, and submit your application form.

    In case of any problem, please contact the training team at