Course: Geocomputation and Machine Learning for Environmental Applications -2023

[Madlene Nussbaum]

Guten Abend

Gerne möchte ich euch auf den interessanten Kurs von Giuseppe aufmerksam machen.

Schöne Samichlous Tag

Madlene



-------- Forwarded Message --------
Subject: 	[Spatial-Ecology] Course: Geocomputation and Machine Learning for Environmental
Applications -2023
Date: 	Mon, 5 Dec 2022 19:28:47 +0100
From: 	Giuseppe Amatulli <giuseppe.amatulli at gmail.com>
To: 	spatial-ecology at lists.osgeo.org



Dear Colleagues,

In view of enhancing computation skills in the geographic domain, Spatial Ecology
<http://spatial-ecology.net/>  is organising a two-month training
course: Geocomputation and Machine Learning for Environmental Applications
<http://spatial-ecology.net/course-geocomputation-machine-learning-for-environmental-applications-intermediate-level-2023/>.

The course will be offered on-line with a supplementary 5-day (or 10-day) in-person
segment at the University of Basilicata, in the magnificent town of Matera
<https://www.google.com/maps/place/75100+Matera,+Province+of+Matera,+Italy/@40.6646012,16.5651092,13z/data=!3m1!4b1!4m5!3m4!1s0x13477ee2482b152b:0x8f6a4ae10da9360!8m2!3d40.666379!4d16.6043199>,
Italy. This is a wonderful opportunity for PhD students, Post-Docs and professionals to
acquire advanced computational skills with a Linux computer.

Please forward to announce this opportunity within your network.

Sincerely, Giuseppe Amatulli  & Spatial Ecology – Team

*Geocomputation and Machine Learning for Environmental Applications
<http://spatial-ecology.net/course-geocomputation-machine-learning-for-environmental-applications-intermediate-level-2023/>.** (April,
May, June, 2023)*

In this course, students will be introduced to an array of powerful
open-source geocomputation tools and machine learning methodologies under Linux
environment. Students who have never been exposed to programming under Linux are expected
to reach the stage where they feel confident in using very advanced open source data
processing routines. Students with a precedent programming background will find the course
beneficial in enhancing their programming skills for better modelling and coding
proficiency. Our dual teaching aim is to equip attendees with powerful tools as well as
rendering their abilities of continuing independent development afterwards. The acquired
skills will be beneficial, not only for GIS related application, but also for general data
processing and applied statistical computing in a number of fields. These essentially lay
the foundation for career development as a data scientist in the geographic domain.

More information and registration:

www.spatial-ecology.net <http://www.spatial-ecology.net/>
twitter: @BigDataEcology

-- 
Giuseppe Amatulli, Ph.D.

Research scientist at
School of the Environment
Yale University
New Haven, CT, USA
06511
Twitter: @BigDataEcology
Teaching: http://spatial-ecology.net
Work:  https://environment.yale.edu/profile/giuseppe-amatulli/
<https://environment.yale.edu/profile/giuseppe-amatulli/>
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