<div dir="ltr"><div class="gmail_quote gmail_quote_container"><div dir="ltr" class="gmail_attr">Dear Colleagues,</div><div dir="ltr"><div><p>
<br>
In view of enhancing computation skills in the geographic domain,
Spatial Ecology is organising: <br>
<br>
A Fall 2025 training Course: <a href="https://spatial-ecology.net/course-geocomputation-machine-learning-for-environmental-applications-intermediate-level-2025/" target="_blank">Geocomputation
and Machine Learning for Environmental Applications
(intermediate level)</a> </p>
<p><a href="https://spatial-ecology.net/course-geocomputation-machine-learning-for-environmental-applications-intermediate-level-2025/" target="_blank">https://spatial-ecology.net/course-geocomputation-machine-learning-for-environmental-applications-intermediate-level-2025/</a>
<br>
<br>
The course will be offered <b>online</b> with a supplementary 5-day
in-person segment at the University of Basilicata, in the
magnificent town of Matera, Italy. <br>
This is a wonderful opportunity for PhD students, Post-Docs and
professionals to acquire advanced computational skills with a
Linux computer. <br>
</p>
<p>Please forward to announce these opportunities within your network.</p>
<br>
Sincerely, <br>
<br>
Giuseppe Amatulli & the Spatial Ecology Team<br>
<br>
Geocomputation and Machine Learning for Environmental Applications
(intermediate level; September, October, November, 2025)<br>
<a href="https://spatial-ecology.net/course-geocomputation-machine-learning-for-environmental-applications-intermediate-level-2025/" target="_blank">https://spatial-ecology.net/course-geocomputation-machine-learning-for-environmental-applications-intermediate-level-2025/</a><br>
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.<br>
<br>
More information and registration: <a href="http://www.spatial-ecology.net" target="_blank">www.spatial-ecology.net</a></div><div><br></div><span class="gmail_signature_prefix">-- </span><br><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div>Giuseppe Amatulli, Ph.D.<br><br>Research scientist at<br>School of the Environment<br>Yale University</div><div>New Haven, CT, USA</div><div>06511</div><div><font color="#000000">Twitter</font><span style="color:rgb(0,0,0)">: @BigDataEcology</span><br><div>
Teaching: <a href="http://spatial-ecology.net" target="_blank">http://spatial-ecology.net</a></div>
Work: <a href="https://environment.yale.edu/profile/giuseppe-amatulli/" target="_blank">https://environment.yale.edu/profile/giuseppe-amatulli/<br></a> <br></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>
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