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Course Criteria
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3.00 Credits
CSCE students complete a comprehensive capstone project during their final year of undergraduate studies. The project is done over 2 semesters in phases: concepts, formal proposal, implementation, and presentation. The projects include and may require the integration of software and human factor, hardware elements and are developed to software engineering methodologies. Prerequisite: CSCE 4561.
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3.00 Credits
Abstraction, proof of correctness, functional languages, concurrent programming, exception handling, dataflow and object oriented programming, denotational semantics. Prerequisite: Graduate standing.
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3.00 Credits
Consideration of current computer engineering topics not covered in other courses. May be repeated for up to 3 hours of degree credit.
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3.00 Credits
Design of computer algorithms, with primary emphasis on the development of efficient implementation.
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3.00 Credits
In-depth introduction to AI. Topics include: philosophical foundations, cognition, intelligent agents, AI languages, search, genetic algorithms, first order and modal logic, inference, resolution, knowledge representation, ontologies, problem solving, planning, expert systems, uncertainty, probabilistic reasoning, fuzzy logic, machine learning, natural language processing, machine vision, and robotics. Prerequisite: Graduate standing.
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3.00 Credits
A study of the principles of formal verification as an alternative to simulation and testing in the elimination of logical design errors in digital systems. Prerequisite: CSCE 2123.
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3.00 Credits
Fault-tolerance is concerned with making or recovering from the effects of faults in a digital system, once they have been detected. On-line fault detection is often required before the fault recovery process. This course will familiarize students with currently available techniques for self-checking and fault-tolerant digital system design.
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3.00 Credits
Topics include: object databases, distributed databases, XML query, data warehouses, network as database systems, peer-peer data sharing architectures, data grids, data mining, logic foundations, semantic databases, spatial and temporal databases, and knowledge bases. Prerequisite: CSCE 5123 and graduate standing.
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3.00 Credits
Application of algorithmic techniques to the analysis and solution of biological problems. Topics include an introduction to molecular biology and recombinant DNA technology, biological sequence comparison, and phylogenetics, as well as topics of current interest. Prerequisite: Instructor consent. (Same as BENG 5213)
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3.00 Credits
An advanced continuation of CSCE 4323. Prerequisite: CSCE 4323 and graduate standing.
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