Sunday, 01 December 2019 at 00:00
Registration:
Registration is CLOSED
The number of participants for each edition is limited. Applicants will be selected according to their experience, qualifications and scientific interest BASED ON WHAT WRITTEN IN THE REGISTRATION FORM.
Attendance is free.
Applicants will receive an email on DECEMBER 16th with response ACCEPTED or NOT ACCEPTED to attend the school.
This course will be held in ENGLISH.
Coordinators: G.Lapenta, F. Delli Ponti, J.Amaya
Teachers: Morris Reidl (Jülich Supercomputer Center/ University of Iceland), Geert Jan Bex (Flanders Supercomputer Center), Peter Wintoft (Swedish Institute of Space Physics), AIDA consortium members.
Description:
AIDA (http://aida-space.eu/) is an European Commission Horizon 2020 project. Its goal is to encourage the use of Artificial Intelligence and Machine learning for the analysis of heliophysics data. We bring together the best european space scientists working in spacecraft observations, simulations, High Performance Computing and machine learning.
The main objective of this school is to introduce the european heliophysics community to the domain of machine learning and data analysis.
Skills:
By the end of the course each student should learn:
Basics of machine learning: supervised, unsupervised learning, neural networks
Space data gathering, handling and processing
What modern techniques are used in the domain of space physics
What modern techniques are used in other applications outside physics
Target Audience
The school is oriented towards established scientists, postdoctoral researchers, phd students and master students in space physics, with an interest in data analysis, who want to learn the basics of machine learning, and find inspiration to apply such techniques to their own research.
Pre-Requisites
Basic knowledge of python, jupyter notebooks, and space physics.
