Mainstream economics is fundamentally neoliberal, employing narratives of meritocracy to explain, normalize, and justify racial capitalism and the inequality and exploitation it inevitability produces. Pluralist economics provides alternative explanations and understandings, directly challenging the conceptualizations, models, methods, values, topics, and pedagogy of economic practice. This sophomore seminar engages students in an exploration of pluralist economics.
Discussion for ECON 111.
A study of the central problem of scarcity and of the ways in which the U.S. economic system allocates scarce resources among competing ends and apportions the goods produced among people. Two 80-minute and one 50-minute lecture/discussion per week.
Requisite for all other courses in Economics.
Fall and spring semesters. The Department.
How to handle overenrollment: Drop students who do not attend the first two classes and admit students from a waiting list.
Discussion for ECON 111.
A study of the central problem of scarcity and of the ways in which the U.S. economic system allocates scarce resources among competing ends and apportions the goods produced among people. Two 80-minute and one 50-minute lecture/discussion per week.
Requisite for all other courses in Economics.
Fall and spring semesters. The Department.
How to handle overenrollment: Drop students who do not attend the first two classes and admit students from a waiting list.
Discussion for ECON 111.
A study of the central problem of scarcity and of the ways in which the U.S. economic system allocates scarce resources among competing ends and apportions the goods produced among people. Two 80-minute and one 50-minute lecture/discussion per week.
Requisite for all other courses in Economics.
Fall and spring semesters. The Department.
How to handle overenrollment: Drop students who do not attend the first two classes and admit students from a waiting list.
Discussion for ECON 111.
A study of the central problem of scarcity and of the ways in which the U.S. economic system allocates scarce resources among competing ends and apportions the goods produced among people. Two 80-minute and one 50-minute lecture/discussion per week.
Requisite for all other courses in Economics.
Fall and spring semesters. The Department.
How to handle overenrollment: Drop students who do not attend the first two classes and admit students from a waiting list.
Open to seniors with consent of the Department.
Spring 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)
Open to seniors with consent of the Department.
Spring 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)
Evolutionary computation techniques harness the mechanisms of biological evolution, including mutation, recombination, and selection, to build software systems that solve difficult problems or shed light on the nature of evolutionary processes. In this course students will explore several evolutionary computation techniques and apply them to problems of their choosing. The technique of genetic programming, in which populations of executable programs evolve through natural selection, will be emphasized.
Information Theory formally studies how to efficiently transmit and store digital information. 4K video streams, high-quality audio from Bluetooth speakers, digital radio, and secure Internet communication are all possible thanks to the solid mathematical foundations of Information Theory.
Randomization is a powerful tool that can be used to design algorithms and data structures that, in many cases, are simpler or more efficient than their deterministic counterparts. Through a combination of implementation and theoretical analysis, students in this course will explore the use of randomization in algorithm design. We will discuss Las Vegas and Monte Carlo algorithms, pseudorandom number generation, and the foundations of probability needed for the analysis of randomized algorithms.
