Essential Math in Environmental Data Science

Master of Environmental Data Science (MEDS)

Summer 2026

Close up montage of the blue point, thinking hard about different ways to calculate an exact slope. In gray text behind them are equations for slope, tangents, delta x, crumpled papers. Finally in the third illustration in the montage, the blue point is holding their arms up in victory with a lightbulb above them and the word 'LIMITS.'

Artwork by Allison Horst

About

Welcome to the course materials for EDS 212 - Essential Math in Environmental Data Science! In this repository you will find all the materials for the Summer 2026 term. This course is part of the UCSB Masters in Environmental Data Science at the Bren School of Environmental Science and Management.

Course Description

Quantitative skills are critical when working with, understanding, analyzing and gleaning insights from environmental data. In the intensive EDS 212 course, students will refresh fundamental skills in basic math (algebra, uni- and multivariate functions, units and unit conversions), differential and integral calculus, differential equations, linear algebra, statistics and probability, and reading, writing and evaluating logical operations.

The goal of EDS 212 (Essential Math in Environmental Data Science) is to prepare incoming MEDS students with quantitative methods, skills, notation and language commonly used in environmental data science and required for their data science courses and projects in the program. By the end of the course, students should be able to:

  • Perform the following by hand: convert units, basic algebra and working with logs and exponentials; write, interpret and evaluate univariate and multivariate functions; basic derivatives and integrals with univariate and multivariate functions; solve simple differential equations; basic operations with scalars, vectors and matrices; writing and evaluating logicals
  • Explain and share examples for how all topics in EDS 212 are useful and used in applied environmental data science
  • Interpret examples of applied math & models from environmental science case studies
  • Work with peers to solve group tasks, then communicate the process of problem solving to the rest of the class

Teaching Team


Instructor

Carmen Galaz García
Email: c_galazgarcia@ucsb.edu
Learn more: Bren profile

TA

Cella Schnabel
Email: cellaschnabel@bren.ucsb.edu
Learn more: Bren profile

Acknowledgements

EDS 212 was originally developed and taught by Allison Horst. It has since been taught and adapted by Ruth Oliver, Sam Shanny-Csik and, most recently, myself, Carmen Galaz García, with contributions from Alessandra Vidal Meza, Cella Schnabel, and Nathan Grimes. This new website houses materials which are reused, adapted, and expanded from, and inspired by the previous instructors’ work.