Course Schedule
The course meets Thursdays, 4:35–7:35 pm. There are 16 calendar weeks but only 13 teaching weeks (2 no-class weeks + 1 field trip week). Slides and readings will be linked as the semester progresses.
Unit 1 — Foundations
| Week | Date | Topic | Slides | Reading |
|---|---|---|---|---|
| 1 | Sep 3 | What is data? What is data science? Intro to R | Week 1 | R4DS Intro |
| 2 | Sep 10 | dplyr basics; into the tidyverse | Week 2 | R4DS Ch. 3–4 |
| 3 | Sep 17 | Getting data: APIs, scraping, joins | Week 3 | R4DS Ch. 7–8 |
| 4 | Sep 24 | Exploratory data analysis; intro to ggplot2 | Week 4 | R4DS Ch. 10–11 |
| 5 | Oct 1 | Advanced ggplot2; principles of effective visualization | Week 5 | R4DS Ch. 12–13 |
Unit 2 — Community Partnership
| Week | Date | Topic | Slides | Reading |
|---|---|---|---|---|
| 6 | Oct 8 | Field trip (no in-class instruction) | — | — |
| 7 | Oct 15 | Chart types and visual communication; project teams + scope confirmed | Week 7 | TBD |
Unit 3 — Spatial Analysis
| Week | Date | Topic | Slides | Reading |
|---|---|---|---|---|
| 8 | Oct 22 | Intro to GIS; Census geography; sf and tidycensus; basic choropleths | Week 8 | TBD |
| 9 | Oct 29 | Advanced GIS; non-Census spatial data; publication-level cartography | Week 9 | TBD |
Unit 4 — Communication
| Week | Date | Topic | Slides | Reading |
|---|---|---|---|---|
| 10 | Nov 5 | Quarto: reports, slides, dashboards; storytelling with data | Week 10 | TBD |
No Class
| Week | Date | Note |
|---|---|---|
| 11 | Nov 12 | No class — instructor at conference |
| 13 | Nov 26 | No class — Thanksgiving |
Unit 5 — Project
| Week | Date | Topic / Milestone |
|---|---|---|
| 12 | Nov 19 | Workday + peer critique — preliminary outputs due |
| 14 | Dec 3 | Draft deliverables due; in-class feedback and revision |
| 15 | Dec 10 | Final polish; presentation prep; semester wrap-up |
| 16 | Dec 17 | Final presentations (in-person) |