Independent reading course. Full course.

Fall and spring semesters. The Department.

This course surveys major topics in the study of economic development. We will examine economic issues pertinent to developing countries through a discussion of economic theory and a review of empirical evidence. The topics covered will include economic growth, structural change, education, health, migration, gender, institutions, aid, and industrial policy. Using publicly available data, students will work on an empirical report identifying key development issues in a country of their choice and analyzing policy recommendations.

In this course, we study the role played by money, banking, and financial markets in the modern economy, with a particular emphasis on how financial intermediation facilitates exchange and how financial conditions promote (or inhibit) economic activity. Specific topics include stock and bond markets, financial institutions and banking regulation, central banking and monetary policy, international finance, and financial crises.

This course surveys the recent wave of financial globalization and assesses both its merits and potential risks. In particular, we will examine the most important potential benefit of financial globalization, an increased rate of economic growth that can be a powerful tool in alleviating poverty. We will analyze the theoretical arguments for a growth-enhancing effect of globalization and discuss the empirical evidence.

Health care poses many pressing questions: Why do we spend so much on health care? Does this spending actually produce better health? How do health care institutions function? What is the appropriate role of government? How are we to judge the efficiency and equity of health care policy? By applying economic analysis to health, health care, and health care markets, health economics provides insight into these questions. In the first section of this course, we will assess the role of health care in the economy and apply economic models to the production of health and health care.

Independent reading course.

Fall and spring semesters. The Department.

This course will explore the algorithms used to create “realistic” three-dimensional computer images. Major topics will include object representations (polygons, curved surfaces, functional models), rendering algorithms (perspective transformations, hidden-surface removal, reflectance and illumination, shadows, texturing), and implementation techniques (scan conversion, ray tracing, radiosity). Students will create images using Pixar's Renderman.

This course will be fully accessible online and may also make use of in-person meetings.

This course addresses the design and analysis of computer algorithms. Topics include: set algorithms such as sorting and searching, graph algorithms, string algorithms, and matrix algorithms. Algorithm design paradigms, including the divide-and-conquer, dynamic programming, and greedy paradigms, will be emphasized. The course will end with a discussion of the theory of NP-completeness and its implications.

This course will be conducted online, with occasional in-person discussion as circumstances allow.

Requisite: COSC 112 and COSC 211. Fall semester. Professor Gardner.

Machine Learning algorithms allow computers to be taught to perform tasks without being explicitly programmed. This course is an introduction to machine learning and data mining. The course will explore supervised, unsupervised, ensemble and reinforcement learning. Topics may include: decision tree learning, rule learning, neural networks, support vector machines, Bayesian learning, clustering, hidden Markov model learning, and/or deep learning. The material of this course has some overlap with that of Computer Science 241, but it is permissible to take both.