Economic theory of the macro-economy. Determinants of unemployment rates, inflation rates, national income, GDP. Tools of public policy available which can be used to promote macroeconomic goals. (Gen.Ed. SB)

The honors section goes beyond the standard study of the micro-economics and addresses some important topical issues such as Market Failure and Income Inequality. The standard textbook is augmented with additional readings related to the environment, health care, employment discrimination and public policy. The development of critical thinking and inquiry is an important part of this course. Therefore, the honors section requires writing assignments that apply theoretical material to real world problems. (Gen. Ed. SB)

An Academic Year-long independent study.

This seminar offers students an opportunity to explore environmental careers that are appropriate for students in environmental conservation, sustainability science, and related fields. We will meet weekly to work on the requested elements for the professional world after graduation, such as resumes, networking, mentoring, interview skills, and more. We will also examine top sectors and growing fields to help students in professional degree programs position themselves for their intended career.

The course will focus on advanced analytical tools for modeling and analysis of modern networks including: network optimization, queuing theory, game theory, mean field theory, and matching theory. Examples of resource allocation problems in ultra-reliable low-latency networks, virtual networks, multi-access edge networks, 5G/6G networks will be discussed by using these tools.

Introduction to the design and analysis of algorithms. Topics include basic algorithmic paradigms (e.g. divide-and-conquer, dynamic programming, the greedy approach and randomization), their application to core problems in graph theory and optimization, as well as analysis of time and space complexity.

Elementary probability theory including random variables, p.d.f., c.d.f., generating functions, law of large numbers. Elementary stochastic process theory including covariance and power spectral density. Markov processes and applications. Prerequisite: E&C-Eng 364 or equivalent.

This course will teach students basic experimental methodologies in electrical and computer engineering required by graduate students. The course will involve hands-on experimentation and and lectures which train students in these areas. A student completing the course will be prepared to complete advanced graduate courses in electrical and computer engineering.