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Course Criteria
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3.00 Credits
Credit to be arranged; not to exceed six credits toward fulfillment of B.S. degree requirements. Prerequisite: Permission of instructor. Includes senior project, and capstone experience. Independent research problems/projects or scholarship activities. The plan of study is negotiated by the faculty member and the student. Contact between the two may be extensive and intensive. Does not include research courses which are theoretical. May be repeated to a total of six credit hours.
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1.00 - 3.00 Credits
1 to 3 credits. Prerequisite: Permission of instructor. Student should have obtained permission of an instructor in the Department of Mathematics and Computer Science prior to registering for this course. Directed independent study of a topic or field of special interest. This may involve readings, research, laboratory or fieldwork, and preparation of papers, as agreed to in advance, by student and instructor. May be repeated to a total of five (5) credit hours.
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6.00 Credits
1 to 3 credits. Student should have obtained permission of an instructor in the Department of Mathematics and Computer Science prior to registering for this course. Lecture course or seminar on a topic or field of special interest, as determined by the instructor. May be repeated to a total of six credit hours.
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3.00 Credits
(3-0) 3 credits. Prerequisite: CSC 300 or permission of instructor. This course covers concepts and techniques within the different phases of the software life cycle: requirements, specifications, design, implementation, testing, operation, and management. The emphasis will be on the study of activities related to software configuration management and maintenance.
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3.00 Credits
(3-0) 3 credits. Prerequisites: CSC 433 or permission of instructor. Topics considered in this course include the viewing/rendering pipeline, interaction strategies, curve and surface models, visible-surface determination, illumination and shading models, antialiasing. Also included will be project development using PHIGS and GKS (C programming required).
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3.00 Credits
(3-0) 3 credits. Prerequisites: Permission of instructor. Low-level processing for extraction of intrinsic image features (edges, range, surface orientation, motion and optical flow, texture), relaxation methods, image segmentation, pattern recognition, geometric and relational structures, knowledge representation, and neural network approaches.
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3.00 Credits
(3-0) 3 credits. Prerequisites: Permission of instructor. The objective of this course is to provide students with a background in advanced artificial intelligence problem solving methods. Topics covered include: Expert systems, fuzzy logic and fuzzy expert systems, genetic algorithms, case-based reasoning, and current research work on new areas of problem solving.
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3.00 Credits
(3-0) 3 credits. Prerequisites: CSC 300 or permission of instructor. This course presents a survey of the architecture and algorithms of neural networks. Topics covered include perceptrons, competitive learning, multi-layer networks, back propagation, and selected topics from pattern recognition.
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3.00 Credits
(3-0) 3 credits. Prerequisites: CSC 456 or permission of instructor. Advanced topics in operating systems design for multiprocessing and distributed systems. Topics will include areas such as methods of interprocess communication, reliability, maintainability, security, and largescale design considerations.
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3.00 Credits
(3-0) 3 credits. Prerequisites: CSC 300 or permission of instructor. This course will include an overview of the relational and entity relationship (E-R) models. It will cover database design, advanced data models, emerging trends in the database field, including data warehouse, data mining, and distributed and parallel databases. Oracle database design tools and programming will be taught.
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