Data Journalism
Overview
This course teaches some of the skills and techniques necessary for obtaining, analyzing and communicating structured information effectively. Students will scrutinize techniques used in previously published projects and will also analyze data on their own, primarily using Excel, HTML, CSS and Javascript (and JS libraries like D3), and, in some cases, command-line tools.
Most classes will begin with a short lecture and discussion about a topic, technique or published piece of journalism that used data journalism.
This will be a technical course, but the primary goal of the course is journalistic; we hope not to get too bogged down in the fiddly bits of the latest technologies. We'll try to demystify the technological side of things so you feel comfortable getting started and thinking programmatically. By the end of the course, you should be able to ask good questions of datasets, get answers from them, and communicate them effectively to a general audience.
Class Schedule
Class meets on Wednesdays from 6:30 to 10 p.m. If you need to get in touch with us outside class time, email to set up a meeting.
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Feb. 4
Getting started: configuring your computers, getting software, hacking 101
Overview of why we’re all here and getting up to speed with github, the terminal, and all the software you'll need. We'll also show how you almost never need to start from scratch. -
Feb. 11
Asking data questions: sort, filter, aggregate, merge
These four skills are 98% of newsroom data analysis. -
Feb. 18
Scraping, cleaning and Excel in the real world
We'll contunie to sharpen our Excel skills, but with data as it actually comes in the world. -
Feb. 25
Let’s publish something
You're going to be publishing on the internet for the rest of your life, so you should know how it works. -
March 4
More coding and styling
Before we build something, let's get some practice with HTML, CSS and Javascript. If there's time, we'll do some journalism too. -
March 11
News applications
It's easy to critique. It's hard(er) to program than we thought. -
March 18
Spring break
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March 25
Keep walking, my friends.
Finishing up the app, and project 1 on 1s. -
April 1
Scraping
Feel the power course through your veins. -
April 8
Charts, project blitz
You don't need to be a graphics editor, but you should know about charts. -
April 15
Project help
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April 22
Project Help
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April 29
Presentations
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May 6
Editing
Useful links
Your Professors
Kevin Quealy — Bald, Minnesotan, talks too much.
Amanda Cox — Sometimes known as the Godfather.
Shadow Professor
Shan Carter — Developed data viz curriculum in 2013; swell guy