Course Catalog - 2022-2023

     

CEVE 543 - ENVIRONMENTAL DATA SCIENCE

Long Title: ENVIRONMENTAL DATA SCIENCE
Department: Civil & Environmental Engr
Grade Mode: Standard Letter
Language of Instruction: Taught in English
Course Type: Lecture
Credit Hours: 3
Restrictions:
Must be enrolled in one of the following Level(s):
Graduate
Description: Introduction to the modeling and analysis of environmental data with a rigorous grounding in probability, optimization, and understanding of underlying physical mechanisms. This course will place a particular focus on the iterative process of building, computing, and critiquing predictive models of environmental processes. Assignments will use the Julia programming language, which will be introduced in the course. Recommended Prerequisite(s): A first course in statistical modeling (STAT 312, STAT 315, CEVE 313, or equivalent) and linear algebra (CAAM 335, MATH 355, or equivalent) is strongly recommended. Additional experience with statistics, optimization, programming, and/or machine learning will prove helpful.