Schedule & Readings

Class Schedule

On Monday and Wednesday we’ll cover new topics and skills, and on Fridays we’ll discuss readings related to those topics. This schedule also includes the topics for the Labs, which will reinforce what we do in class.

I will add Lab links to Github Classroom assignments before each week’s lab. You’ll find a guide to using Github Classroom here.

Date Mon./Wed. Topics Lab Fri. Discussion
  Module 1: Data Basics    
Jan. 17-21 What Is Data?; Textbook Ch. 12 Garlic Mustard: 01, 03 Beyond the Hype
Jan. 24-28 NO CLASS MONDAY; Metadata and the Data Analysis Cycle; R Basics Book Reviews: 01, 03 No class: One-on-one meetings
Jan. 31-Feb. 4 Data Wrangling; Textbook Ch. 5 Movie Dialogue: 01, 03 Ethics, Bias, and Diversity
Feb. 7-11 Visualizing Data; Textbook Ch. 3 Code Glossary I: 01, 03 Ugly, Bad, and Wrong Figures
  Module 2: Describe    
Feb. 14-18 Exploratory Data Analysis; Textbook Ch. 7; Hypothesis Testing Substance Use: 01, 03 An unprecedented Nintendo leak turns into a moral dilemma for archivists
Feb. 21-25 Hypothesis Testing Audiobooks: 01, 03 Stop Misusing P-Values; Science Isn’t Broken
Feb. 28-Mar.4 Resampling US Congress I: 01, 03 Ethics, Bias, and Diversity
  Module 3: Predict    
Mar. 7-11 Linear Regression US Congress II: 01, 03 The Happiness Calculator, So About That Thermometer Data
Mar. 21-25 Multiple Regression Airbnb: 01, 03 Wine and Math
Mar. 28-Apr.1 Network Analysis Marvel Comics: 01, 03 & Code Glossary II Outlier Conference
Apr. 4-8 Mapping and Spatial Data Final Project Launch: 01, 03 NO CLASS; Complete Ethics Certification
Apr. 11-15 Text Data; Textbook Ch. 14 Project Sprints The Numbers Don’t Speak for Themselves
  Module 4: Communicate    
Apr. 18-22 Debugging; Open Data Practices Project Sprints Sweet & Slim, Greasy & Grim, Embrace the Grind
Apr. 25-29 Student Presentations Project Sprints Student Presentations
May 2 Wrap-up & Advice for Future Students Troubleshooting and Questions