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Artificial Intelligence for Earth Monitoring MOOC

Artificial Intelligence for Earth Monitoring MOOC

EUMETSAT, ECMWF, Mercator Ocean International and the EEA have jointly developed a new massive open online course (MOOC) on Artificial Intelligence (AI) and Earth monitoring, and we are proud to be part of this project!

Artificial intelligence and machine learning (ML) are undoubtedly becoming more and more present in our daily lives, proving important contributions to different fields, like farming, healthcare, and finance, to name a few. In a fast-changing and critical time for Earth Observation (EO), especially for those involved in its use for climate and meteorology, there is huge potential for AI and ML.

This new MOOC starting October 18 offers you a comprehensive overview of the Copernicus Programme and the wealth of EO data it provides, as well as how AI and ML are transforming the interpretation of EO data.

As well as video content, in this MOOC there is also a strong hands-on element with the inclusion of a series of specially-developed Jupyter notebooks that will guide people through the process of working with Copernicus data and new and exciting machine learning algorithms. 

The notebooks are put together using Python and give examples of the different types of Copernicus data (ocean, atmosphere, land and climate) and machine learning algorithms.

To make it easier to follow the notebooks, they are accompanied by dedicated video tutorials that have been produced to explain the content of the notebooks. 

Registration is now open!

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International AI Future Lab on AI4EO Follow

International AI Future Lab on Artificial Intelligence for Earth Observation @TU_Muenchen, @BMBF_bund funded

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Retweet on Twitter International AI Future Lab on AI4EO Retweeted
Avatar Xiaoxiang ZHU @xiaoxiang_zhu ·
16 Jan

Interested in multimodal and #hyperspectral #RemoteSensing? check our #MDAS benchmark dataset @Zhu_XLab recently published with @ESSD_journal: https://essd.copernicus.org/articles/15/113/2023/
Data: https://mediatum.ub.tum.de/1657312
Code: https://zenodo.org/record/7428215#.Y8UlWHaZOhE
A collaboration with @DLR_de @GFZ_Potsdam #AI4EO

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Avatar International AI Future Lab on AI4EO @ai4eo_de ·
13 Dec

Check the work of our lab @Zhu_XLab about audiovisual learning by @koheidler @MouLichao @xiaoxiang_zhu and our collaborators!

Konrad Heidler @koheidler

Check out our paper on the topic, out now at
https://www.sciencedirect.com/science/article/pii/S1569843222003181 (2/2)

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Retweet on Twitter International AI Future Lab on AI4EO Retweeted
Avatar Zhu Lab @zhu_xlab ·
22 Nov

Take a look at our recent paper by @gawlikowskij @PWJEbel @xiaoxiang_zhu et al on how clouds affect #EarthObservation downstream applications. #AI4EO https://twitter.com/PWJEbel/status/1594977731309191169

Patrick Ebel @PWJEbel

Curious how clouds affect remote sensing applications, such as land cover classification? @gawlikowskij, Michael Schmitt at @unibw_m, @xiaoxiang_zhu and me provide an analysis and interpretation of the effects of cloud coverage!

Check out https://ieeexplore.ieee.org/document/9956865

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