Here you will find all availble EECS courses listed alphabetically. The tabs above futher organize the courses by the starting letter of the course name. If there is a courses that you cannot find listed, or have questions about a course that are not answered by the courses description feel free to Contact Us.
Description and analysis of the key components in optical communications systems. Topics covered include quantum sources, propagation and dispersion characteristics of fiber, receiver characteristics, and system gain considerations.
Prerequisite(s): EECS 220 and PHSX 313 or equivalent and upper-level EECS eligibility
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The course will focus on fundamental theory and various methods and applications of fiber-optic measurements and sensors. Topics include: optical power and loss measurements, optical spectrum analysis, wavelength measurements, polarization measurements, dispersion measurements, PMD measurements, optical amplifier characterization, OTDR, optical components characterization and industrial applications of fiber-optic sensors.
Prerequisite(s): EECS 628 or equivalent.
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Formal language generation by grammars, recognition by automata (finite and pushdown automata, Turing machines), and equivalence of these formulations; elementary containment and closure properties. Emphasis on context-free, deterministic context-free and regular languages.
Prerequisite(s): EECS 510 or equivalent.
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Introduction to information technology and the computer as a general tool processing information. Topics include internet tools (including browsers, search engines and web page construction), networking, computer organization, algorithms, programming languages, data representation and manipulation, binary numbers and Boolean logic, system and application software (including word processors, spreadsheets and presentation software), operating systems, databases, artificial intelligence, social and ethical issues in computing, information security, and mobile computing
Prerequisite(s): MATH 101 or MATH 104 or eligibility to enroll in MATH 115 or MATH 121.
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Basic concepts and techniques in the design and analysis of computer algorithms. Models of computations. Simple lower bound theory and optimality of algorithms. Computationally hard problems and the theory of NP-Completeness. Introduction to parallel algorithms.
Prerequisite(s): EECS 560 and either EECS 461 or MATH 526
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Basic information about expert systems: architecture of an expert system, building expert systems, uncertainty in expert systems, taxonomy of expert systems. Knowledge representation: first order logic, production systems, semantic nets, frames. Uncertainty in expert systems, one-valued approaches: probability theory, systems using Bayes' rule and systems using certainty theory; two-valued approaches: systems using Dempster-Shafer theory and system INFERNO; set-valued approaches: systems using fuzzy set theory and systems using rough set theory.
Prerequisite(s): EECS 560 or consent of instructor
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