I taught the following courses at the University of Mississippi during the 2018-2022 academic years. Syllabi for each course are available for download via the links below:
(Instructor, Fall 2021) Syllabus
This course is designed to familiarize new graduate students with the fundamentals of conducting research in political science. We will begin the first half of the class by examining some critical basic concepts in the philosophy of science before turning to more specific problems of constructing (and critiquing) research design, including the general problem of determining the observable implications of social science theory, and the more individualized issues of sampling, measurement, and interpretation of findings. In the second half of the class, we will walk through practical matters of crafting a research design, including the process of formulating specific hypotheses from a research topic, the specifics of data collection and management for different types of research designs, and concluding with an examination of the process of writing up and presenting research.
(Instructor, Fall 2021, Fall 2020, Fall 2019, Fall 2018) Syllabus
This course is an introduction to the political and legislative process of the United States Congress. The course will focus on a half-semester-long legislative simulation in which students will play the role of United States Senators. Students will organize the legislature, form parties and caucuses, select their own leaders, draft their own bills, debate, and vote on legislation. The first part of the course will consist of traditional lectures to familiarize students with how Congress works; the rest of the semester will be primarily devoted to the legislative simulation.
(Instructor, Spring 2021, Fall 2019, Spring 2018) Syllabus
The ability of political science research to shed light on pressing questions in contemporary political life is only as strong as the quality of the research designs used by political scientists. Gaining and sharing insight into the behavior of human beings within the sphere of politics requires a strong understanding of the logic of causal inference underlying empirical research in the social sciences, a capacity to gather useful political data and analyze it in an informed manner, and the ability to share research with others through scientific papers and formal presentations. This course will cover all of these aspects of social science research and leave students with the basic toolkit to ask good questions and design and execute plans to answer those questions. While this course is predominantly focused on quantitative research methods, qualitative methods will be discussed to a lesser degree. This course is appropriate for political science majors who wish to gain a foundation in political science research methods as well as non-majors who simply wish to gain a better understanding of social science research.
(Instructor, Spring 2021, Spring 2020, Spring 2019) Syllabus
This course is an introduction to the political and administrative processes of the American presidency. The spring of 2021 marks the start of President Biden's first term in office. Like all new presidents, he will pursue an agenda for the nation by presenting policy goals to Congress, his party, and the American people, staffing his administration, making appointments to the judiciary and high-ranking positions in the bureaucracy, and taking unilateral action, all within the context of a highly polarized political environment. In this class, we will substantively examine the constitutional second branch of government as a political institution nestled in a complex political system of rival actors, and apply analytical political science concepts to explain and evaluate the behavior of the Biden administration's first 100 days in office. Students are expected to apply this knowledge through several short assignments and reports on contemporary executive politics in order to critically assess theories of executive branch politics.
(Instructor, Fall 2020) Syllabus
This course covers a selection of work in political science on the role of the presidency as a political institution and its relationship of the American federal executive with other political institutions and the public. The weekly progress of the course will focus on building familiarity with a core collection of books and readings as well as a collection of detailed summaries of these works for future reference. Along with this deliverable, the major course assignments will require students to review a recent published article on executive politics and both develop and present a research proposal grounded in one of the topics listed in the syllabus. Taken as a whole, these activities should allow students to leave the class with a familiarity with recent and important theoretical approaches, empirical strategies, and supported results regarding major questions about executive politics in the United States.
(Instructor, Spring 2020, Fall 2018, Summer 2017, Summer 2013, Summer 2012) Syllabus
The currents of American political life are defined by the constraints that enduring political institutions apply to channel evolving public opinion. Much of the tumult in American politics we see today can be understood through consideration of the foundations of American government, major political institutions, and mechanisms that link citizens and government. This course will examine how the government of the United States is organized, the rationale behind its organization, and the ways citizens, political actors, and political institutions interact to achieve political goals. This course is appropriate for political science majors who wish to gain a foundation in American politics as well as for non-majors who simply wish to gain a better understanding of American government and processes.
(Condensed Graduate Workshop - Instructor Spring 2021, Spring 2019, Spring 2018)Syllabus
Perception and reasoning by intelligent systems requires the processing of inputs into a reasonable mapping of the world, learning from experience, and management of the uncertainty that pervades the world around us. This course will provide a firm introduction to machine learning and the design of intelligent systems capable of handling these three tasks. The course will engage with machine learning by developing the theoretical and mathematical underpinnings of a variety of algorithms, and apply successful algorithms in several contexts to witness their limitations and strengths. This course is appropriate for graduate students and computer science undergraduates comfortable with programming who have basic training in probability theory and familiarity with linear algebra and calculus.
Probability and Inference; Linear Models (Graduate); Maximum Likelihood Estimation (Graduate) ;
Introduction to Python; Text as Data (Graduate)
Introduction to Game Theory