Schedule

🗓️ Course Schedule

subject to change

Week Topic Tools
Preliminaries
1 Course Introduction Scripts; R and RStudio
2 A Guide to Your Computer Markup Languages; Quarto
3 File Management & Version Control Filesystems; git; GitHub
4 A Field Guide to Data Data Formats; surveys, readr; tidyr
5 Structural Data Manipulation dplyr; srvyr
6 Data Visualization I Grammar of Graphics; ggplot2
7 Data Visualization II ggplot2
8 Core Exam (Thursday, October 15)
9 Workflow & Data Retrieval tidycensus; APIs; database/SQL overview
10 Social Networks & Network Data iGraph; statnet
11 Cartography tidyverse mapping; color scales; projection
12 Geographic Data sf; tigris; mapgl; osm
13 Grab Bag: Statistics, Text, & Working with AI Loops, t.test(), lm(), glm()
14 Project Presentations
F Finals Week (Project Due)

Advanced Topics (If we get to them)

Week Topic Tools
Text Data & Data Scraping
Statistical Models
Missing Data
Web Apps & Visualization quarto, shiny
Programming with AI Claude Code
Local LLMs
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🗒️ Logistical Notes

All content may be found linked from the course content pages. Readings and content are posted for the whole semester, so students may look ahead if they wish. Typically, each week has two class days: the first, a lecture, and the second, a workshop. Each workshop day typically has some computing tasks, reference reading or other material, and a data assignment.

What to expect

Each week of class is organized into a learning module. Each learning module covers a topic relevant to data wrangling, management, and visualization, and goes in three phases: lecture, workshop, and assignment.

  1. Lectures: Each module’s material is first presented through lectures given Tuesday. Occasionally, there will be an at-home workshop to complete as well. You should start every week with these. Each week has companion readings and reference materials for those wishing to dive deeper.
  2. Workshops: Each module’s material is then reinforced through a workshop in our Thursday class session.
  3. Assignment: Each module concludes with an applied assignment (typically, a problem set, but occasionally something else - a practicum or project). The module’s assignment is due the week after the module in class, and we will go over solutions together the day it is due.

Workshops (Live Class Sessions)

During workshop sessions, we cover material in the following order:

  1. Go over solutions and material for the assignment due that week. Sometimes, this will primarily involve the professor covering solutions, but other times, it will involve students presenting their work on that week, as well. Be prepared to ask questions and talk about your assignments.1
  2. Conduct hands-on coding sessions for material in the current week’s module.
  3. Allow for time to begin the assignment for the current week’s module, ask the professor questions, etc.

Where to find materials and how to navigate the course

Each learning module can be accessed here, on the class website. We’ll use Blackboard for initial assignment submission before transferring to GitHub a few assignments in. All course materials may be found here, with the exception of some that contain proprietary or copyrighted material that must be kept behind a login.

Footnotes

  1. Note that means the cadence will feel odd at first: the assignment given during Thursday workshop week 1 is due during Thursday workshop week 2, and thus, we’ll go over the assignment given during week 1 during week 2 but after we’ve already had the week 2 lecture, etc. It’s done this way to make sure you always have a full week to work on the assignment.↩︎