new edition of my remixed data science textbook

18 August 2023 - kudos:

I’m happy to share that the Fall 2023 edition of my remixed Introduction to Data Science textbook is now available on my website. This book adapts material from the “ModernDive” Statistical Inference via Data Science course, Catherine D’Ignazio and Lauren Klein’s excellent Data Feminism, a number of other Creative Commons-licensed works, and some of my own contributions to put together a no-cost, openly-licensed textbook for my data science students. I put together the first edition of this book for last Fall’s version of this course, but the first run through taught me a lot, and I’m very happy about this edition (though I do have a small laundry list of errors to fix, and I’d like to eventually get into some fiddlier bits like removing social media icons from the header).

why 'open access' isn't enough

6 July 2022 - kudos:

I just barely microblogged something about what I want to say here, but over the past hour, it’s been nagging at me more and more, and I want to write some more about it. I was introduced to academia through educational technology, and I was introduced to educational technology through a class at BYU taught by David Wiley. This class was not about educational technology, but David’s passion for Web 2.

6 July 2022 - kudos:

This summer, I’m remixing an alternative textbook for my Fall intro to data science class, and I’m pleasantly surprised by how helpful Creative Commons-licensed journal articles are proving. Shows that “open access” is only part of license’s benefits.

16 September 2021 - kudos:

Unsatisfied with the Intro to Data Science textbook I’ve inherited. Fortunately, an earlier version is Creative Commons-licensed, as are some other fantastic resources. Guess who’s going to remix himself a new textbook for next Fall!