Course schedule

Week	Date	Topic	Technical Reading	Critical/Cultural Reading	Tasks	Assignment
Week 1		Introductions
		Command Line & Files, Files, Files	*Read The Command Line	*Read and annotate “The Yellow Wallpaper,” Charlotte Perkins Gilman (Perusall)	*Fill out intro survey
		Introduction to Python & GitHub	*Read How To Use Jupyter Notebooks		*Download and install Anaconda *Make a GitHub account *Download GitHub Desktop *Download VSCode	HW 1 Due
Week 2		Python — Variables & Data Types	*Read Variables, Data Types	*Read and annotate “Introduction,” Data Feminism, Catherine D’Ignazio and Lauren Klein (Perusall)	*Install Jupyter Variable Inspector
		Python — Files, Character Encoding, String Methods	*Read Files and Character Encoding	*Read and annotate “I Can Text You A Pile of Poo, But I Can’t Write My Name,” Aditya Mukerjee (Perusall)
		Python — String Methods	*Read String Methods			HW 2 Due
Week 3		Python — Conditionals & Comparisons	*Read Conditionals & Comparisons	*Read and annotate “(Re)Humanizing Data: Digitally Navigating the Bellevue Almshouse” Anelise Hanson Shrout (Perusall)
		Python — Lists & Loops	*Read Lists & Loops
		Python — Lists & Loops	*Read Lists & Loops Part 2	*Read and annotate “What Gets Counted Counts,” Data Feminism, Catherine D’Ignazio and Lauren Klein (Perusall)		Homework 3 Due
Week 4		Python — Dictionaries, Functions	*Read Dictionaries, Functions	*Read and annotate “Unicorns, Janitors, Ninjas, Wizards, and Rock Stars,” Data Feminism, Catherine D’Ignazio and Lauren Klein (Perusall)
		Dictionaries, Functions	*Read Dictionaries, Functions
		Object-Oriented Programming
Week 5		Python Review		*Read and annotate “The Numbers Don’t Speak For Themselves” Data Feminism, Catherine D’Ignazio and Lauren Klein (Perusall)		Homework 4 Due
		Wellness Day
		Data Analysis — Pandas	*Read Pandas Basics	*Read “Data Biographies,” Heather Krause	Fill out midterm project preferences
Week 6		Data Analysis — Pandas		*Read and annotate “Markup Bodies: Black [Life] Studies and Slavery [Death] Studies at the Digital Crossroads” Jessica Marie Johnson (Perusall)
		Data Analysis — Pandas		*Read and annotate “Film Dialogue from 2,000 screenplays, Broken Down by Gender and Age,” Hannah Anderson and Matt Daniels (Perusall) * Read Film Dialogue FAQ
		Data Analysis — Pandas	* Review Pandas Basics Parts 1-3	* Watch “From Story-time to Send Off: Inside The Pudding’s Process,” Caitlyn Ralph * Recommended Reading: “Why the Pandemic Experts Failed,” Robinson Meyer and Alexis C. Madrigal	Gather process ideas for your group’s midterm project
Week 7		Data Analysis — Pandas	* Review Pandas Basics Parts 1-3	* Read “Datasheets for Datasets,” Timnit Gebru, et al. * Recommended Reading: “Timnit Gebru’s Exit From Google Exposes a Crisis in AI,” Alex Hanna and Meredith Whitaker	Pick a question that interests you from “Datasheets for Datasets” and be prepared to talk about it
		Data Analysis — Pandas Review
		Data Collection — Web Scraping	* Review “Web Scraping Part 1”	* Read “The Largest Vocabulary in Hip-Hop,” Matt Daniels * Listen to Missy Elliott’s Under Construction (at least a few songs)		Midterm Project Due
Week 8		Data Collection — Web Scraping/APIs	* Review “Web Scraping Part 2”	* Read and annotate “The Secretive Company That Might End Privacy as We Know It,” Kashmir Hill (Perusall)
		Data Collection — APIs		* Read “An Illustrated Introudction to APIs,” Xavier Adam
		Data Collection — APIs		* Read and annotate “Narrative Paths and Negotiation of Power in Birth Stories,” Maria Antoniak, David Mimno, and Karen Levy (Perusall)
Week 9		Text Analysis	* Review TF-IDF	* Read and annotate excerpts of The House on Mango Street, Sandra Cisneros (Perusall)
		Text Analysis	* Review TF-IDF	* Recommended Reading: “Seven Ways Humanists Are Using Computers to Understand Text,” Ted Underwood (older version of blog post, formatting not broken)
		Text Analysis	* Review Topic Modeling Overview	* Read “Beyond Canonical Texts: A Computational Analysis of Fanfiction,” Smitha Milli and David Bamman * Check out the Fan Engagement Meter		Homework 5
Week 10		Text Analysis	* Review Topic Modeling Text Files	* Read and annotate “Dimensions of Scale: Invisible Labor, Editorial Work, and the Future of Quantitative Literary Studies,” Lauren Klein (Perusall)
		Text Analysis	* Review Named Entity Recognition * Play with GPT-2
		Text/Network Analysis		* Read and explore “Introduction,” “A Multimedia Literary Analysis,” (Sections 1-3), Lost in the City: An Exploration of Edward P. Jones’s Short Fiction, Kenton Rambsy and Peace Ossom-Williamson		Homework 6 Due
Week 11		Network Analysis	* Read “Demystifying Networks” (Part I), Scott Weingart	* Read and annotate “Network of Thrones,” Andrew Beveridge and Jie Shan (Perusall) * Recommended: Game of Thrones: Beginner’s Guide (spoilers) * Recommended: Season 1, Episode 2 of Game of Thrones
		Network Analysis	* Read “Demystifying Networks (Part II)”, Scott Weingart			Homework 7 Due
		Wellness Day
Week 12		Wellness Day
		Mapping		* Read and annotate “How an internet mapping glitch turned a random Kansas farm into a digital hell,” Kashmir Hill (Perusall)
		Mapping		* Explore Torn Apart / Separados, Manan Ahmed, Alex Gil, Moacir P. de Sá Pereira, Roopika Risam, Maira E. Álvarez, Sylvia A. Fernández, Linda Rodriguez, and Merisa Martinez * Read ‘ICE Is Everywhere’: Using Library Science to Map the Separation Crisis, Emily Dreyfuss
Week 13		How to Make Arguments and Tell Stories With Data		* Read “Trucks and Beer,” John Miller
		How to Make Arguments and Tell Stories With Data		* Read “Topic Modelling Martha Ballard’s Diary,” Cameron Blevins
		How to Make Arguments and Tell Stories With Data		* Re-read “Beyond Canonical Texts: A Computational Analysis of Fanfiction,” Smitha Milli and David Bamman		Final Project Proposal Due
Week 14		How to Make Arguments and Tell Stories With Data		* Read “Mapping the State of the Union,” Mitch Fraas and Ben Schmidt * Read How Americans Think About Climate Change, in Six Maps, Nadja Popovich, John Schwartz and Tatiana Schlossberg
		How to Make Arguments and Tell Stories With Data		* Gendered Language in Teacher Reviews, Ben Schmidt
		Last Day				Dataset Biography Due
						Final Project Due