The United States is in an unprecedented period of rising inequality. This course begins by examining the history of inequality in the U.S. since the start of the twentieth century. It then uses cutting-edge and detailed national data to document and explore the current state of inequality and intergenerational mobility in the U.S. We consider inequality by various metrics, such as race, gender, and geography, and in various outcomes, such as income, wealth, health, educational attainment, and incarceration.

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.

Open to seniors with consent of the Department.

Fall semester. The Department.

How to handle overenrollment: null

Students who enroll in this course will likely encounter and be expected to engage in the following intellectual skills, modes of learning, and assessment: (none specified)

Independent reading course.

Fall and spring semesters. The Department.

How to handle overenrollment: null

Students who enroll in this course will likely encounter and be expected to engage in the following intellectual skills, modes of learning, and assessment: (none specified)

Independent reading course.

Fall and spring semesters. The Department.

How to handle overenrollment: null

Students who enroll in this course will likely encounter and be expected to engage in the following intellectual skills, modes of learning, and assessment: (none specified)

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.

Requisite: COSC 112 and COSC 211. Admission with consent of the instructor. Fall semester: Professor Gardner.

How to handle overenrollment: null

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.

Requisite: COSC 112 and COSC 211. Admission with consent of the instructor. Fall semester: Professor Gardner.

How to handle overenrollment: null

Computing networks are ubiquitous and used for a broad range of purposes. Networks are often complex and dynamic, connecting systems with a range of capabilities. Some computers are permanently connected while others (e.g., mobile devices) routinely leave and rejoin the network. In any case, the network must ensure that data are delivered quickly and reliably from one computer to another. This course will begin with the problem of communicating between two computers, followed by the problems of building generalized networks for different types and varying numbers of computing devices.

This course will provide students with a deeper understanding of modern computer systems and hardware platforms, including design principles for desktop CPUs, mobile devices, graphics processing units (GPUs), and flexible computing platforms (e.g., FPGAs).  Key topics include multi-core processing, hardware acceleration, software-hardware co-design, and memory management.  This course includes a laboratory component and projects developing and interacting with hardware platforms.  

This course will provide students with a deeper understanding of modern computer systems and hardware platforms, including design principles for desktop CPUs, mobile devices, graphics processing units (GPUs), and flexible computing platforms (e.g., FPGAs).  Key topics include multi-core processing, hardware acceleration, software-hardware co-design, and memory management.  This course includes a laboratory component and projects developing and interacting with hardware platforms.