<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Ryan Avery on The Carpentries</title><link>https://deploy-preview-705--carpentries-website.netlify.app/blog/author/ryan-avery/</link><description>Recent content in Ryan Avery on The Carpentries</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Mon, 18 Nov 2024 23:02:38 -0500</lastBuildDate><atom:link href="https://deploy-preview-705--carpentries-website.netlify.app/blog/author/ryan-avery/index.xml" rel="self" type="application/rss+xml"/><item><title>Teaching a New Geospatial Python Lesson</title><link>https://deploy-preview-705--carpentries-website.netlify.app/blog/2020/03/teaching-a-new-geospatial-python-lesson/</link><pubDate>Tue, 10 Mar 2020 00:00:00 +0000</pubDate><guid>https://deploy-preview-705--carpentries-website.netlify.app/blog/2020/03/teaching-a-new-geospatial-python-lesson/</guid><description>&lt;p>On February 6-7, 2020, the &lt;a href="https://develop.larc.nasa.gov/about.php">NASA DEVELOP program&lt;/a> at Jet Propulsion Laboratory(JPL) hosted the initial run of &lt;a href="https://carpentries-incubator.github.io/geospatial-python/">Introduction to Geospatial Raster and Vector Data with Python&lt;/a>, a Carpentries incubator lesson. This lesson was imagined as a Python complement to &lt;a href="https://datacarpentry.org/r-raster-vector-geospatial/">Introduction to Geospatial Raster and Vector Data with R&lt;/a>, an existing Data Carpentry lesson.&lt;/p>
&lt;p>&lt;a href="http://www.kunalmarwaha.com/">Kunal Marwaha&lt;/a> and &lt;a href="https://github.com/rbavery">Ryan Avery&lt;/a>, the lesson authors, served as instructors. We had 8 attendees; the small learner size helped us work through hiccups in the new material. Most attendees were recent graduates in a field related to remote sensing or geographic information systems. We had a range of previous experience level, including folks who use Python daily, weekly, and never.&lt;/p></description></item><item><title>Two Workshops at NASA DEVELOP (or, Python De-Fanged)</title><link>https://deploy-preview-705--carpentries-website.netlify.app/blog/2017/07/nasa-2/</link><pubDate>Tue, 11 Jul 2017 00:00:00 +0000</pubDate><guid>https://deploy-preview-705--carpentries-website.netlify.app/blog/2017/07/nasa-2/</guid><description>&lt;p>&lt;b>This post originally appeared on the &lt;a href="https://software-carpentry.org/">Software Carpentry website.&lt;/a>&lt;/b>&lt;/p>
&lt;p>On 8-9 June, 2017, Katie Moore, Deputy Data Management Team Lead for the &lt;a href="https://ceres.larc.nasa.gov/">NASA CERES&lt;/a> Science Team, and
Ryan Avery, Geoinformatics Fellow with the &lt;a href="https://develop.larc.nasa.gov/">NASA DEVELOP National Program&lt;/a>,
ran a Self-Organised workshop in Hampton, VA.&lt;/p>
&lt;p>On 12-13 June, 2017, Kunal Marwaha, a software engineer with Palantir, Kelly Meehan, Geoinformatics Fellow with NASA DEVELOP, and Ryan ran another
Self-Organised workshop in Norton, VA.&lt;/p>
&lt;p>Both workshops focused on building skills in NASA DEVELOP participants, who work on 10-week feasibility projects
that demonstrate how to apply NASA Earth observations to environmental concerns to enhance
project partner decision-making. In the process, both partners and participants gain a better understanding
of NASA&amp;rsquo;s Earth-observing (EO) capabilities and improve their professional and technical capacity to use EO data.
For Katie, Kelly, and I, these were the first workshops in which we taught entire lessons
and we found it to be an extremely rewarding experience.&lt;/p></description></item></channel></rss>