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Course Criteria
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3.00 Credits
Introduction to programming language concepts, including issues of design, specification, representation, and implementation across a range of language types (procedural, object-oriented, functional, declarative, and parallel). Specific topics will include models of computation and their influence on language design, syntax, semantics and abstract interpretation, language structures, type theories, and program transformation methods, such as interpretation, compilation, partial evaluation, and graph reduction. Prerequisites: Computer Science 221 and 261, or consent of instructor. (4 credits)
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3.00 Credits
Draws on the student's general background in mathematics to construct models for problems arising from such diverse areas as the physical sciences, life sciences, political science, economics, and computing. Emphasis will be on the design, analysis, accuracy, and appropriateness of a model for a given problem. Case studies will be used extensively. Specific mathematical techniques will vary with the instructor and student interest. Prerequisites: Mathematics 312, and Computer Science 121 or 123. Alternate fall semesters; next offered Fall 2009. (4 credits)
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3.00 Credits
Transforms and their applications. Topics selected from among: the Fourier transform and applications in partial differential equations and signal and image processing; the Laplace transform in control theory; wavelet analysis. Prerequisites: Mathematics 236 and 312. Alternate spring semesters; next offered Spring 2009. (4 credits)
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3.00 Credits
An introduction to the field of parallel processing and its three major subareas of parallel architectures, parallel languages, and parallel algorithms. Topics include SIMD and MIMD systems, private memory and shared memory designs, dataflow architectures; issues in parallel language design such as process creation and management, message passing, synchronization, and deadlock; the design and formal analysis of parallel algorithms in areas such as sorting, searching, numerical methods, and graph theory. Students will design and implement software for an actual parallel processing system. Prerequisites: Computer Science 240 and 221, or consent of instructor. (4 credits)
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3.00 Credits
Topics in applied mathematics chosen from: cryptography; complexity theory and algorithms; integer programming; combinatorial optimization; computational number theory; applications of geometry to tilings, packings, and crystallography; applied algebra. Prerequisites: Mathematics 236 and 379 and Computer Science 121 or 123. Alternate fall semesters; next offered Fall 2008. (4 credits)
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3.00 Credits
An introduction to the topology of Euclidean, metric, and abstract spaces. Covers the fundamental ideas from point set topology- continuity, convergence, and connectedness-as well as selected topics from knot theory,three-dimensional manifolds, fixed-point theory, the fundamental group, and elementary homotopy theory. Prerequisite: Mathematics 236 and Mathematics 377. Alternate fall semesters; next offered Fall 2008. (4 credits)
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3.00 Credits
Topics in algebra to be chosen from: group representations; algebraic coding theory and finite fields; Galois theory; algebraic and transcendental numbers; ring theory; applied algebra. Prerequisite: Mathematics 376. Alternate fall semesters; next offered Fall 2009. (4 credits)
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3.00 Credits
A continuation of Real Analysis including discussion of basic concepts of analysis with particular attention to the development of the Riemann and Lebesgue integrals. Introduction to metric spaces, Fourier analysis. Prerequisite: Mathematics 377. Alternate spring semesters; next offered Spring 2009. (4 credits)
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3.00 Credits
Algebra of complex numbers, analytic functions, the Cauchy-Riemann equations, Cauchy's theorem, the Cauchy integral formula, Taylor and Laurent series, the residue theorem, and conformal mapping. Prerequisite: Mathematics 377 or 437. Alternate spring semesters; next offered Spring 2010. (4 credits)
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3.00 Credits
This course will introduce students to the design, implementation, and analysis of databases stored in database management systems (DBMS). Topics include implementation-neutral data modeling, database design, database implementation, and data analysis using relational algebra and SQL. Students will generate data models based on real-world problems, and implement a database in a state-of-the-art DBMS. Students will master complex data analysis by learning to first design database queries and then implement them in a database query language such as SQL. Advanced topics include objects in databases, indexing for improved performance, distributed databases, and data warehouses. Prerequisites: Computer Science 225, or consent of instructor. Alternate spring semesters; next offered Spring 2010. (4 credits)
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