Fwd: [Spatial-Ecology] Course: Geocomputation and Machine Learning for Environmental Applications.

[Madlene Nussbaum]

Salut zäme
Giuseppe bietet ein Kurs zur Anwendung von maschinellem Lernen an.
Liebe Grüsse
Madlene



-------- Forwarded Message --------
Subject: 	[Spatial-Ecology] Course: Geocomputation and Machine Learning for Environmental
Applications.
Date: 	Tue, 11 Jan 2022 14:04:15 -0500
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/geocomp_ml_2022-announcement/>.

The course will be offered on-line with a supplementary 5-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/geocomp_ml_2022-announcement/>.** (April, May, June, 2022)*

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
Tweeter: @BigDataEcology
Teaching: http://spatial-ecology.net <http://spatial-ecology.net/>
Work:  https://environment.yale.edu/profile/giuseppe-amatulli/
<https://environment.yale.edu/profile/giuseppe-amatulli/> 

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