Research for a thesis of approximately 50 written pages undertaken in the fall semester of the fourth year by archaeology majors who have been accepted into the Interdisciplinary Archaeology Distinguished Majors Program. Prerequisite: acceptance into Archaeology DMP

This course introduces students to a variety of disciplinary approaches to the study of Europe (history, anthropology, sociology, political science, economics, and culture). Stress will be laid on how combining perspectives from different fields of study can help deepen understanding of specific problems of European life. Emphasis on student interpretation of readings and analysis of central issues in Europe's development across time.

Provides a foundation in discrete mathematics, data structures, algorithmic design and implementation, computational complexity, parallel computing, and data integrity and consistency. Case studies and exercises will be drawn from real-world examples (e.g., bioinformatics, public health, marketing, and security).

Provides an in-depth exploration of probabilistic and statistical methods used to understand, quantify, and manage uncertainty. Learn foundational concepts in probability and statistics, simulation techniques, and modern approaches to parameter estimation, decision theory, and hypothesis testing. Topics include parametric and nonparametric methods, Bayesian and frequentist paradigms, and applications of uncertainty in real-world problems. 

Instruction on key events, places, texts and thinkers that help us understand the history and principles of democracy.

This course is an introduction to clinical ethics, which concerns the identification, analysis, and resolution of ethical problems arising in patient care. The course deals with two tiers of ethical problems occurring frequently in the clinical setting: those that are present in every clinical encounter and special problems that arise with particular patients.

Independent research for undergraduate students enrolled in the BA/BS/MPH 5 year program or other programs that may be related to Public Health or Ethics.

Comprehensive introduction to predictive modeling, a cornerstone of data science and machine learning. Learn the fundamental concepts, techniques, and tools used to build models while emphasizing both theoretical understanding and practical applications. The topics include we will cover are an in-depth analysis of linear models and different variants, their extension to generalized linear models, and an introduction to nonparametric regression.

This course introduces first-year graduate students in the humanities and social sciences to the knowledge and skills fundamental to success in graduate school. Particular topics vary.

Consider the effect of public opinion on policy in the U.S. What do policymakers believe about citizens' preferences? Whose opinion matters, when does it matter, & why? Do policies always reflect the majority? How has partisan polarization affected policy-making in recent years? Examine questions through lens of some of today's most pressing issues, including immigration policy, social welfare programs, military spending, abortion, & more.