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Course Criteria
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3.00 Credits
This course addresses security issues for TCP/IPbased and NT networks. Access control and communications security issues will be covered as well as Internet and intranet security. Prerequisite: CS 457, MIS 420, or permission of instructor.
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3.00 Credits
Application of networking concepts related to the wide area networks. Includes topics related to nature and use of wide area networks including topologies, software and hardware. Special emphasis on the TCP/IP Suite of Protocols. Prerequisite: CS 457, MIS 420, or permission of the instructor.
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3.00 Credits
A comparative study of programming languages and their features. The course is aimed at developing an understanding of the organization of programming languages, especially the run-time behavior of programs. Students will gain experience with a variety of languages. Prerequisite: CS 245 and one other programming language course.
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3.00 Credits
Formal treatment of programming language interpreter, translator, and compiler design concepts. Topics include lexical analysis, parsing, code generation, and code optimization. Emphasis will be on the theoretical aspects of parsing context-free languages, translation specifications, and machineindependent code improvement. Programming projects that demonstrate various concepts will be assigned. Prerequisite: CS 461.
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3.00 Credits
Introduction to programming on the Internet. Prerequisite: CS 131 and CS 145, equivalent, or permission of instructor.
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3.00 Credits
To extend the students' knowledge and practice in analysis, design, and programming of computer networks. Prerequisites: CS 245 and 328.
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3.00 Credits
A general introduction to the theories and problems involved in the development of computer-based intelligence systems with specific emphasis on knowledge representation and search. The focus will be on artificial intelligence research that provides information for the understanding of human intelligence and on application research in areas such as expert systems, natural language systems, and intelligent computer-aided instruction.
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3.00 Credits
An interdisciplinary investigation of the foundations of human knowledge representation and understanding, the functioning of the human mind, and how these impact on recent computer technologies. Cross-listed as: Psy 472 and Phil 472.
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3.00 Credits
Basic Neurobiology; Neural Networks; Single Neuron Models; Single Layer Perceptrons; Multi- Layer Perceptrons; Radial Basis Function networks; Committee machines; Kohonen networks; Applications of neural networks. Prerequisites: CS 245 and Math 273.
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3.00 Credits
This course studies different machine learning techniques/paradigms, including decision trees, neural networks, genetic algorithms, Bayesian learning, rule learning, and reinforcement learning. The applications of these techniques to problems in data analysis, knowledge discovery and data mining are discussed. Prerequisites: CS 245, Math 320, Math 345 recommended.
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