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ESCI 506: Environmental Data Science Studio

Environmental Sciences · 2 credits

Environmental Data Science Studio is a graduate-level, two-credit course designed to give students hands-on experience with core data science tools and applications used in environmental research and analysis. This flipped studio course covers essential topics with a different focus each quarter. E.g., data visualization, data wrangling, open-source project management, app development, machine learning, etc. The studio format emphasizes collaborative, practical learning in each session. Repeatable to a maximum of 6 credits, including original course.

Offered in 6 of the 26 listed terms (Fall 2025 to Spring 2027).

Prerequisites

None that Banner enforces.

From Banner's catalog for Spring 2027. Banner lists only the requisites it enforces, so check the catalog entry too.

Required by (0)

No course lists it as a prerequisite.

Syllabi and course websites

None listed yet.

Instructors

InstructorSectionsTerms
Bunn, Andy5Fall 2025 to Spring 2027
Bunn, Rebecca1Fall 2026

Every offering in the listed terms (6 sections)

TermSecCRNTypeMeetsInstructorEnrolledDelivery
Spring 20270
ReproducibleWorkflow Data Mgmt
22926LectureW 8:00am-9:50am · ES 534Bunn, Andy0/20Face to Face Instruction
Winter 20270
EnvDataSci: Machine Learning
12996LectureW 8:00am-9:50am · ES 318Bunn, Andy0/20Face to Face Instruction
Fall 202600
EnvDataSci: Data Wrnglng & Viz
43094LectureF 8:00am-9:50am · ES 318Bunn, Rebecca10/20Face to Face Instruction
Spring 202600
EnvDataSci: Dashbrd & App Dev
23583LectureW 8:00am-9:50am · AW 302Bunn, Andy6/20Face to Face Instruction
Winter 20260
EnvDataSci: Machine Learning
13849LectureW 8:00am-9:50am · ES 318Bunn, Andy9/20Face to Face Instruction
Fall 202500
EnvDataSci: Data Wrnglng & Viz
44002LectureM 8:00am-9:50am · ES 318Bunn, Andy9/20Face to Face Instruction