Climate change is an urgent and multifaceted challenge facing all of society.
Harvard faculty teach an expanding array of courses examining the many dimensions of this shared challenge. Explore courses in climate and sustainability ranging from economics and English to public health and climate science.
HARVARD UNIVERSITY
THE SALATA INSTITUTE FOR CLIMATE AND SUSTAINABILITY
The MBA course on "Risks, Opportunities, and Investments in an Era of Climate Change" offers a unique and comprehensive curriculum aimed at preparing the next generation of entrepreneurs, leaders, and investors to succeed in a rapidly changing economic landscape. This course is ideal for students who aspire to become entrepreneurs by starting their own company or joining a start-up that is driving innovation and solving challenges posed by climate change. Additionally, the course will benefit those who wish to lead or advise firms on transitioning their operations and business models to become more sustainable and innovative. Finally, the course will be beneficial to students seeking to understand the full spectrum of climate opportunities pursuing a career in venture capital, private equity, or public markets investing.
The connection between diet and patient health is unequivocal, yet nutrition-based interventions in medical practice remain significantly underutilized. The aim of this course is for you to understand the health and economic consequences of the lack of nutrition education and practice in medicine, and to demonstrate the unique potential for physicians and other health care professionals to serve as change agents for effectively integrating nutrition into medical care.
The purpose of this course is to introduce students to the complexities of and best practices for community engaged/action research and collaboration. Students will integrate skills and knowledge from their environmental health training to address community interests/needs.
This course will examine major issues of water resources (i.e. water sources, supply, quality, treatment, use, distribution and storage, policy) in the developing world at various geographic locations and scales.
This winter session travel course will introduce students to the intersections of climate change, air quality and health for populations in the Eastern Mediterranean region. Students will apply epidemiological tools to examine environmental exposures and health vulnerabilities that are unique to this region.
This course will challenge your assumptions about the world’s populations as you discover surprising similarities and unexpected differences between and within countries.
Provides students with the opportunity to review the epidemiologic basis for associating selected occupational and environmental exposures with health outcomes and to explore how this science might be used to develop and implement regulation of these exposures.
This course examines application of epidemiologic methods to environmental and occupational health problems. Objectives are to review methods used in evaluating the health effects of physical and chemical agents in the environment, to review available evidence on the health effects of such exposures, and to consider policy questions raised by the scientific evidence.
This course is geared toward graduate students from all schools, but open to passionate undergraduates interested in exploring the implications of global environmental change on nutrition, infectious disease, mental health, and other domains of wellbeing. Throughout the course of the semester, students will engage in diverse materials from many types of examples of planetary health research, from nutrition and mental health, to infectious and non-communicable diseases.
This course covers applied advanced regression analysis. Its focus is on relaxing classical assumptions in regression analysis to better match what epidemiological data really looks like. Specifically, the course will cover nonlinear exposure-response relationships and repeated measure designs, including non-parametric and semi-parametric smoothing techniques, generalized additive models, quantile regression, and time series models.
