Applied Data Science & Visualization

CDAE 7990 · Graduate Seminar · Fall 2026

Students working at computers in a Vermont classroom in autumn

Course Overview

This course introduces students to data science and visualization as tools for understanding complex social, economic, and environmental questions. Students learn R for data wrangling, spatial analysis, and reproducible reporting, with an emphasis on producing work that is useful to real audiences.

A core component is a semester-long applied project delivered to an external community partner.


Logistics

Instructor Andrew Van Leuven, Assistant Professor
Department Community Development & Applied Economics (CDAE), UVM Extension
Meets Thursdays, 4:35–7:35 pm
Semester Fall 2026
Computing Posit Cloud
Primary language R

Textbook

We follow R for Data Science (2nd ed.) by Hadley Wickham, Mine Çetinkaya-Rundel, and Garrett Grolemund — available free online.


Course Units

Unit Weeks Theme
1 1–5 Foundations: R, tidyverse, EDA, ggplot2
2 6–7 Community Partnership: field trip + project launch
3 8–9 Spatial Analysis: GIS, Census data, cartography
4 10 Communication: Quarto reports, slides, dashboards
5 12, 14–16 Project: workdays, critique, final presentations

Community Partner

Our applied project partner is a regional economic and community development organization. Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris.

See the Project page for team assignments and deliverables.


Full course policies, grading, and expectations are on the Syllabus page.