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EDS 212

Essential Math for Environmental Data Science

Instructors:
Ruth Oliver
Samantha 'Sam' Csik

Prerequisites: None

Units: 2

Description

 

Quantitative Analysis in Environmental Data Science

Quantitative skills and understanding 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), derivative and integral calculus, differential equations, linear algebra, and reading, writing and evaluating logical operations.

Learning Objectives

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 and in R: 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

 

Course Syllabus: Summer 2024 

Course Website 

 

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