Our teaching portfolio at Boston University covers concepts, theories, and methods needed in environmental policy careers and sought-after for entry-level positions. This includes environmental statistics, economics, open-source GIS, spatial data science, machine learning, and empirical causal inference.

EE 508 Data Science for Conservation Decisions

Application of quantitative methods to support conservation decisions. Ecosystem value mapping, systematic conservation planning, policy instrument design, rigorous impact evaluation, decision theory, data visualization. Implementation in state-of-the-art open- source software. Real-life case studies from the U.S. and abroad. A perennial capstone favorite for students in environment analysis & policy (EAP) and data science.

Course website with syllabus and evaluations

EE 545 Methods for Environmental Policy Analysis

Our environmental economics course. A rigorous introduction to the economic analysis of environmental policy, and to the implications of the special character of environmental problems for public decision making. It introduces the tools available to environmental policy makers, and develops quantitative frameworks for analyzing their effectiveness, advantages, and disadvantages.

EE 270 Data, Models, and Analysis in Earth & Environment

Our environmental statistics course. It introduces key questions, types and sources of data, and analytical methods in Earth and Environment, and introduces students to an array of quantitative methods from both the natural- and social-science disciplines.