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 Ethics, Bias, and Diversity
Feb. 7-11 Visualizing Data; Textbook Ch. 3 Code Glossary I Ugly, Bad, and Wrong Figures
  Module 2: Describe    
Feb. 14-18 Exploratory Data Analysis; Textbook Ch. 7; Hypothesis Testing Substance Use An unprecedented Nintendo leak turns into a moral dilemma for archivists
Feb. 21-25 Hypothesis Testing Audiobooks Stop Misusing P-Values; Science Isn’t Broken
Feb. 28-Mar.4 Resampling US Congress I So About That Thermometer Data
  Module 3: Predict    
Mar. 7-11 Linear Regression US Congress II The Happiness Calculator
SPRING BREAK      
Mar. 21-25 Multiple Regression Airbnb Wine and Math
Mar. 28-Apr.1 Network Analysis Marvel Comics/Code Glossary II The Numbers Don’t Speak for Themselves
Apr. 4-8 Mapping and Spatial Data Final Project Launch NO CLASS; Complete Ethics Certification
Apr. 11-15 Text Data; Textbook Ch. 14 Project Sprints Sweet & Slim, Greasy & Grim
  Module 4: Communicate    
Apr. 18-22 Debugging; Open Data Practices Project Sprints Embrace the Grind
Apr. 25-29 Student Presentations Project Sprints Student Presentations
May 2 Wrap-up & Advice for Future Students Troubleshooting and Questions