Syllabus

Applied Data Science & Visualization · CDAE 7990 · Fall 2026

Under Construction

This syllabus is a draft placeholder. Content is incomplete and subject to change. Do not rely on anything here.

Course Description

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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.

Student Learning Outcomes

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After completing this course the student will be able to:

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What Does This Class Look Like?

Class Format

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Attendance Policy

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General Classroom Expectations

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Required Course Materials

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

Computing: Posit Cloud. A workspace will be set up before the semester begins with required packages and shared datasets. Students use the Cloud Free plan; the instructor covers per-student fees.

[Additional materials TBD.]

Course Site

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Grading Policy

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Item	Weight
Homework / Lab Assignments	TBD
Community Partner Project	TBD
Participation	TBD
Other TBD	TBD

Use of Generative AI Tools

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Communication

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Accommodations & University Policies

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Schedule

See the Schedule page for the full week-by-week breakdown.