History of Finance
The aim of this course is to provide a historical and institutional account of the development and evolution of finance. In particular, we will study how certain financial theories and instruments came out, focusing on the major episodes of crises that have occurred around the world. The course is divided in three main parts. The first part covers early episodes of financial crises and speculative bubbles, starting from the "Tulip Mania" up until the late 19th century. The second part focuses on "The Great Depression" and its aftermath, up until the 1970s.
Introduction to Communication Studies
Introduction to Public Health
The field of Public Health integrates knowledge of biology, human behavior, and social constructs with problem-solving strategies to address issues of disease facing distinct populations. This course will provide an introduction to principles of public health and epidemiology, social determinants of health, the biological basis of the most prevalent communicable and non-communicable diseases, as well as an exploration of global public health issues.
Survey of Art History II
Climate Change Science, Policy and Advocacy
This course focuses broadly on climate change science and policy, that is, the physical causes of climate change and how humans act, or fail to act, on that knowledge. After a survey of policy-relevant climate change science in the first part of the course, our attention turns to the ways scientific knowledge, worldviews, and power affect climate change decision-making at the international level as carried out by the United Nations.
Asia: Beyond the Great Wall
Biostatistics: Dealing with Data
A fundamental aspect of practicing biology-related science (be it through the lens of ecology, medicine, public health, etc.) is dealing with data. Data analysis requires much more than picking the correct statistical test. Data sets are being generated at an exponential rate and the potential for combining public data sets to ask new scientific questions is immense. In this course, we will learn to use the free, open-source software program R (the industry standard) for cleaning, organizing, and analyzing biological data sets (including data visualization).