Diplomacy in the Americas is an academically based community-service course where students explore what it means to educate youth for global civic and political engagement. Students apply theoretical and pedagogical principles in curriculum design, classroom teaching, and collaborative learning with public high school students on the topics of Latin American politics and the role of the Organization of American States (OAS). Analyzing and strategizing like a diplomat and guided by theories of democracy and the other three OAS pillars of economic development, security, and human rights, students will collectively examine and propose solutions to the most pressing issues in the Americas. This course is also an SNF Paideia Program Course.

The Trump Presidency has profoundly shifted America's role in the world and the way in which key institutions of foreign policy making are staffed and positioned to advance America's interests. The ascent of extreme nationalists and nationalism in other power centers in the world along with growing distrust in government and public institutions may have marked the close of the two-decade post 9/11 era. Indeed, the global COVID-19 pandemic and the ways in which actors across the international spectrum have responded (or failed to respond) has led many to question the assumptions inherent in the post-9/11 international order and has marked the beginning of a new era of competition, a return to great-power politics, and the diminishing power of traditional actors, systems, and ideals on the global stage. This course will provide students with an in-depth, practical analysis of foreign policy and foreign policy making, with a view from Washington. It will also provide a baseline global literacy, through the lens of emerging ideas, institutions, interests, and actors, and focus on a framework for understanding shifts already underway in how Washington views the world. We will utilize less traditional resources, and instead focus on practical and "real-world" course material as well as less traditional instruction methods - utilizing and analyzing the sources and resources that policy makers in Washington rely upon. These include long-form journalism, official government documents, hearings and Congressional debate, think tank products, and news sources. Students will have the opportunity to engage with a variety of guest-speakers, all of whom have held senior official and non-governmental roles in American foreign policy making and influencing. Guest speakers will provide unique insight into their own experiences at the highest levels of foreign policy making and advocacy, and offer guidance as to how to pursue careers in foreign policy, national security, and international development. In the past, guest speakers have included: Former Deputy Secretaries of State William Burns and Heather Higginbottom; Executive Director of the ONE Campaign; Former Director of Policy Planning at the State Department; Former Ambassadors, Senior Professional Staff from the House Committee on Foreign Affairs and Senate Foreign Relations Committee, former Assistant Secretary of Population, Refugees, and Migration, among others.

How do the Constitution's checks and balances work in practice? And where are they not working? This course examines the fault lines between Washington's two most powerful institutions - Congress and the President - how they clash, and where they work together. Students learn how Congress and the President share and compete for power in lawmaking, spending, investigations, nominations, foreign policy, and impeachment. The course is designed to foster skills in formulating strategies for conducting policy in an environment of institutions competing for power.

Designed to complement a policy internship, this two credit course will focus on content and skills that are likely to be useful in typical Washington offices. Students will develop literacy on the most pressing domestic policy topics and will work on writing and presentation skills. All students will participate in a public policy internship for at least ten hours a week.

This course is designed as a follow-up to PSCI 1800. In that class students learn a great deal about how to work with individual data sets in R: cleaning, tidying, merging, describing and visualizing data. PSCI 1801 shifts focus to the ultimate goal of data science: making inferences about the world based on the small sample of data that we have. Using a methodology that emphasizes intuition and simulation over mathematics, this course will cover the key statistical concepts of probability, sampling, distributions, hypothesis testing, and covariance. The ultimate goal of the class is for students to have the knowledge and ability to perform, customize, and explain bivariate and multivariate regression. Students who have not taken PSCI-1800 should have basic familiarity with R, including working with vectors and matrices, basic summary statistics, visualizations, and for() loops.

Understanding and interpreting large datasets is increasingly central in political and social science. From polling, to policing, to economic inequality, to international trade, knowing how to work with data will allow you to shed light on a wide variety of substantive topics. This is a first course in a 4-course sequence that teaches students how to work with and analyze data. This class focuses on data acquisition, management, and visualization, the core skills needed to do data science. Leaving this course, students will be able to acquire, input, format, analyze, and visualize various types of political and social science data using the statistical programming language R. While no background in statistics or political science is required, students are expected to be generally familiar with contemporary computing environments (e.g. know how to use a computer) and have a willingness to learn a variety of data science tools. Leaving this class, students will be prepared to deepen their R skills in PSCI 3800, and then use their R skills to learn statistics in PSCI 1801 and 3801. They will also be ready to use their R skills in courses in other disciplines as well.

Understanding and interpreting large datasets is increasingly central in political and social science. From polling, to policing, to economic inequality, to international trade, knowing how to work with data will allow you to shed light on a wide variety of substantive topics. This is a first course in a 4-course sequence that teaches students how to work with and analyze data. This class focuses on data acquisition, management, and visualization, the core skills needed to do data science. Leaving this course, students will be able to acquire, input, format, analyze, and visualize various types of political and social science data using the statistical programming language R. While no background in statistics or political science is required, students are expected to be generally familiar with contemporary computing environments (e.g. know how to use a computer) and have a willingness to learn a variety of data science tools. Leaving this class, students will be prepared to deepen their R skills in PSCI 3800, and then use their R skills to learn statistics in PSCI 1801 and 3801. They will also be ready to use their R skills in courses in other disciplines as well.

Understanding and interpreting large datasets is increasingly central in political and social science. From polling, to policing, to economic inequality, to international trade, knowing how to work with data will allow you to shed light on a wide variety of substantive topics. This is a first course in a 4-course sequence that teaches students how to work with and analyze data. This class focuses on data acquisition, management, and visualization, the core skills needed to do data science. Leaving this course, students will be able to acquire, input, format, analyze, and visualize various types of political and social science data using the statistical programming language R. While no background in statistics or political science is required, students are expected to be generally familiar with contemporary computing environments (e.g. know how to use a computer) and have a willingness to learn a variety of data science tools. Leaving this class, students will be prepared to deepen their R skills in PSCI 3800, and then use their R skills to learn statistics in PSCI 1801 and 3801. They will also be ready to use their R skills in courses in other disciplines as well.

Understanding and interpreting large datasets is increasingly central in political and social science. From polling, to policing, to economic inequality, to international trade, knowing how to work with data will allow you to shed light on a wide variety of substantive topics. This is a first course in a 4-course sequence that teaches students how to work with and analyze data. This class focuses on data acquisition, management, and visualization, the core skills needed to do data science. Leaving this course, students will be able to acquire, input, format, analyze, and visualize various types of political and social science data using the statistical programming language R. While no background in statistics or political science is required, students are expected to be generally familiar with contemporary computing environments (e.g. know how to use a computer) and have a willingness to learn a variety of data science tools. Leaving this class, students will be prepared to deepen their R skills in PSCI 3800, and then use their R skills to learn statistics in PSCI 1801 and 3801. They will also be ready to use their R skills in courses in other disciplines as well.

Understanding and interpreting large datasets is increasingly central in political and social science. From polling, to policing, to economic inequality, to international trade, knowing how to work with data will allow you to shed light on a wide variety of substantive topics. This is a first course in a 4-course sequence that teaches students how to work with and analyze data. This class focuses on data acquisition, management, and visualization, the core skills needed to do data science. Leaving this course, students will be able to acquire, input, format, analyze, and visualize various types of political and social science data using the statistical programming language R. While no background in statistics or political science is required, students are expected to be generally familiar with contemporary computing environments (e.g. know how to use a computer) and have a willingness to learn a variety of data science tools. Leaving this class, students will be prepared to deepen their R skills in PSCI 3800, and then use their R skills to learn statistics in PSCI 1801 and 3801. They will also be ready to use their R skills in courses in other disciplines as well.