[Spatial-Ecology] Course: Geocomputation and ML + GEO-OPEN-HACK

[Info Spatial Ecology]

Dear Colleagues,

In view of enhancing computation skills in the geographic domain, 
Spatial Ecology  is organising two events:

1) A two-month training course: *Geocomputation and Machine Learning for 
Environmental Applications (intermediate level) 
<https://spatial-ecology.net/course-geocomputation-machine-learning-for-environmental-applications-intermediate-level-2024/>.*

The course will be offered online with a supplementary 5-day in-person 
segment at the University of Basilicata, in the magnificent town of 
Matera, Italy.
This is a wonderful opportunity for PhD students, Post-Docs and 
professionals to acquire advanced computational skills with a Linux 
computer.

2) Shortly after the aforementioned Matera in-person workshop, we are 
co-hosting from 24 to 28 June
"GEO-OPEN-HACK-2024: Big Geospatial Data Hackathon with Open 
Infrastructure and Tools (advance level)"
with the International Institute for Applied Systems Analysis (IIASA) in 
Laxenburg, Austria.
*Graduates from the Spatial Ecology course will be directly admitted to 
the GEO-OPEN-HACK-2024*.
Details will be announced shortly.

Please forward to announce these opportunities within your network.

Sincerely,

Giuseppe Amatulli  & the Spatial Ecology Team


*Geocomputation and Machine Learning for Environmental Applications. 
(April, May & June, 2024)*
https://spatial-ecology.net/course-geocomputation-machine-learning-for-environmental-applications-intermediate-level-2024/*
<https://spatial-ecology.net/course-geocomputation-machine-learning-for-environmental-applications-intermediate-level-2024/>*
On this course, students will be introduced to an array of powerful 
open-source geocomputation tools and machine learning methodologies in 
the Linux environment. Students who have never been exposed to 
programming in Linux will acquire confidence in using advanced open 
source data processing routines. Those with a programming background 
will find the course beneficial in improving their programming and 
modelling skills. We aim to equip attendees with powerful programming 
tools, as well as hone their abilities for independent development. This 
will be valuable not only for GIS related applications but also for 
general data processing and applied statistical computing in a number of 
fields. We strive to provide the best grounding for career development 
as a geographic data scientist.

More information and registration: www.spatial-ecology.net
(Apply before Saturday 28 January 2023 for an early bird discount)

twitter: @BigDataEcology

-- 

___________
Dr. Giuseppe Amatulli,
Director of Spatial Ecology
g.amatulli at spatial-ecology.net
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