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Course Criteria
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3.00 Credits
Study of security and information assurance in stand-alone and distributed computing. Topics include ethics, privacy, access control methods and intrusion detection. Fall, even years.
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3.00 Credits
An advanced study of computer algorithms not covered in CPSC 223 along with principles and techniques of computational complexity. Topics could include dynamic programming, B-trees, minimum spanning trees, the Floyd-Warshall algorithm, various string matching algorithms, computational geometry, Np-completeness and reducibility. Spring odd years.
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3.00 Credits
An introduction to applied cryptography. Topics could include classical cryptosystems (shift, affine, Vigenere, Playfair, Enigma), modern cryptosystems (DES, AES, RSA, El Gamal), key exchange protocols, digital signatures, security protocols, and zero-knowledge techniques, along with their applications in e-commerce and intelligence. Spring, even years.
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3.00 Credits
An introduction to the study of discrete nonlinear dynamical systems and their chaotic behavior. The course will focus on investigation s through computer experiments- both numerical and graphical- and the corresponding mathematical analysis of the observed behavior. A significant portion of the course will be devoted to designing graphics programs. In the humanistic tradition of Gonzaga, students will also learn the historical development of the modern science of chaotic dynamical systems. Spring even years.
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3.00 Credits
Topics that reflect the current interests and expertise of the faculty. Possible topics include complexity theory, mathematical modeling, sensor networks, genetic algorithms, neural networks and data mining. On sufficient demand.
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1.00 - 4.00 Credits
Topics that reflect the current interests and expertise of the faculty. Possible topics include complexity theory, mathematical modeling, sensor networks, genetic algorithms, neural networks and data mining. On sufficient demand
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1.00 - 3.00 Credits
Topics that reflect the current interests and expertise of the faculty. Possible topics include complexity theory, mathematical modeling, sensor networks, genetic algorithms, neural networks and data mining. On sufficient demand
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3.00 Credits
Topics that reflect the current interests and expertise of the faculty. Possible topics include complexity theory, mathematical modeling, sensor networks, genetic algorithms, neural networks and data mining. On sufficient demand
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1.00 - 3.00 Credits
Topics that reflect the current interests and expertise of the faculty. Possible topics include complexity theory, mathematical modeling, sensor networks, genetic algorithms, neural networks and data mining. On sufficient demand
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1.00 - 3.00 Credits
Topics that reflect the current interests and expertise of the faculty. Possible topics include complexity theory, mathematical modeling, sensor networks, genetic algorithms, neural networks and data mining. On sufficient demand
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