<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Book Review on The Carpentries</title><link>https://deploy-preview-705--carpentries-website.netlify.app/blog/tag/book-review/</link><description>Recent content in Book Review 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/tag/book-review/index.xml" rel="self" type="application/rss+xml"/><item><title>And Now There Are Three</title><link>https://deploy-preview-705--carpentries-website.netlify.app/blog/2016/10/and-now-there-are-three/</link><pubDate>Tue, 04 Oct 2016 00:00:00 +0000</pubDate><guid>https://deploy-preview-705--carpentries-website.netlify.app/blog/2016/10/and-now-there-are-three/</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>A new book has just been published that covers much of the same material as Software Carpentry,
and a great deal more:
Paarsch and Golyaev&amp;rsquo;s
&lt;em>&lt;a href="https://www.amazon.com/Introduction-Effective-Computing-Quantitative-Research/dp/0262034115/">A Gentle Introduction to Effective Computing in Quantitative Research: What Every Research Assistant Should Know&lt;/a>&lt;/em>.
It covers almost everything I would want to see in a one-semester course for new research students:
the Unix shell,
data organization,
the basics of Python,
data analysis,
&amp;ldquo;geek stuff&amp;rdquo; (including hardware and algorithm analysis),
numerical analysis,
some worked examples,
Python extensions,
and preparing manuscripts with LaTeX.&lt;/p></description></item></channel></rss>