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700 Level

20 CS 701: Computer Science Seminar

1 Graduate
Required of all full time graduate students. Offered in Fall quarter. Organization. Local, and visiting speakers.

20 CS 702: Computer Science Seminar

1 Graduate
Required of all full time graduate students. Offered in Winter quarter. Organization. Local, and visiting speakers.

20 CS 703: Computer Science Seminar

1 Graduate
Required of all full time graduate students. Offered in Spring quarter. Organization. Local, and visiting speakers.

20 CS 723: Topics in Artificial Intelligence

3 Graduate
Introduction to varying topics in artificial intelligence.

20 CS 724: Logic in Artificial Intelligence

3 Graduate
A survey of algorithms for logic inference. Logic inference is a particularly important NP-complete problem. It is often important in its own right (as in AI). Also, logic is based upon a natural (and ancient) mode of expression, and reducing other NP problems to prepositional logic is very often straightforward ?saving one the effort of writing tailored solvers for other NP problems. Prereq.: 20-CS-633, 634 and 15-CS-621.

20 CS 727: Uncertainty in AI

3 Graduate
Computational models for management of uncertainty.

20 CS 735: Computer Security I

3 Graduate
Conventional and public key cryptography. Elementary theory of numbers. Digital signatures. Voting schemes. Provably secure cryptosystems based on computationally hard problems. Multiparty protocols and zero-knowledge proofs. Multiprescision arithmetic using Prof. D. Schmidt's implementation of the Arbint class in C++. Cryptology: The analysis and cracking of cryptosystems and protocols. Some famous, some infamous and some not so well known examples of cracked systems and protocols. Quantum computers that crack uncrackable codes. Quantum cryptography: using quantum mechanics to guarantee secrecy.

20 CS 736: Computer Security II

3 Graduate
Conventional and public key cryptography. Elementary theory of numbers. Digital signatures. Voting schemes. Provably secure cryptosystems based on computationally hard problems. Multiparty protocols and zero-knowledge proofs. Multiprescision arithmetic using Prof. D. Schmidt?s implementation of the Arbint class in C++. Cryptology: The analysis and cracking of cryptosystems and protocols. Some famous, some infamous and some not so well known examples of cracked systems and protocols. Quantum computers that crack uncrackable codes. Quantum cryptography: using quantum mechanics to guarantee secrecy.

20 CS 743: Computer Networking

3 Graduate
This course introduces basic concepts for Computer Networking. Many underlying issues related to multiple layered information transmission in a computer network, will be covered. This course requires a group simulation project that implements a concept in computer networking.

20 CS 747: Complexity Theory

3 Graduate
Polynomial-time complexity. Cook's theorem and NP-complete problems, the polynomial-time hierarchy, and other complexity classes.

20 CS 749: Computability Theory

3 Graduate
Recursive function theory and Turing machines, unsolvable problems, recursively innumerable sets, and the arithmetic hierarchy.

20 CS 765: Computer Graphics 2

3 Graduate
Advanced topics in computer graphics, such as algorithms for scan-line generation, hidden surface removal, shading and texturing, and anti-aliasing.

20 CS 766: User Interface II

3 Graduate
Exploration of the current and emerging technologies/methodologies that support the design, implementation, and applications of advanced multimedia systems.

20 CS 769: Computational Geometry

3 Graduate
Selected topics in computer-aided geometric design (CAGD). Sample topics include differential and combinational geometry, algorithms for free-form curves and surfaces, and feature-based surface design.

20 CS 780: Self-Study Research

1-6 Undergraduate
Research study not directly related to the thesis or dissertation. Self-study to determine the research area and topic.
Credits may not be counted towards MS/PhD program.
Credits arranged each quarter.

20 CS 781: Advanced Algorithms I

3 Graduate
Formal treatment of algorithms and algorithms design methodologies; both sequential and parallel paradigms will be covered. Measures of parallel complexity. Program complexity and correctness proofs.

20 CS 782: Advanced Algorithms II

3 Graduate
Study of sequential, parallel and distributed algorithms. Complexity classes NP-complete, P-complete, NC. Approximation algorithms. Network reliability, routing and flow algorithms. Probabilistic algorithms. Distributed algorithms. Internet algorithms.

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