Our teaching portfolio at Boston University covers concepts, theories, and methods that are useful 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 270 Data, Models, and Analysis in Earth & Environment

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.

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.

EE 535 Global Land Conservation: Theory and Practice

In-depth treatment of the theory and practice of global land conservation. Global drivers of ecosystem degradation. Scale and effectiveness of public and private responses. Implementation of instruments, including regulatory, market-based, community-driven, and supply-chain approaches. International and domestic case studies.

EE 545 Methods for Environmental Policy Analysis

This course is 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.