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Course Criteria
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3.00 Credits
General investigation of the field of expert systems. The first part of the course is devoted to designing expert systems. The last half of the course is implementation of the design and construction of demonstration prototypes of expert systems. Prerequisite: CSCI262, MATH/CSCI358. 3 hours lecture; 3 semester hours.
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3.00 Credits
Linear regression, analysis of variance, and design of experiments, focusing on the construction of models and evaluation of their fit. Techniques covered will include stepwise and best subsets regression, variable transformations, and residual analysis. Emphasis will be placed on the analysis of data with statistical software. Prerequisites: MATH323 or MATH335. 3 hours lecture; 3 semester hours.
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3.00 Credits
This course will discuss methods for building and solving both continuous and discrete mathematical models. These methods will be applied to population dynamics, epidemic spread, pharmcokinetics and modeling of physiologic systems. Modern Control Theory will be introduced and used to model living systems. Some concepts related to self-organizing systems will be introduced. Prerequisite: MATH225 or MATH235. 3 hours lecture, 3 semester hours.
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3.00 Credits
Modern methods for constructing and evaluating statistical models. Topics include generalized linear models, general116 Colorado School of Mines Undergraduate Bulletin 2008-2009 ized additive models, hierarchical Bayes methods, and resampling methods. Prerequisites: MATH335 and MATH424. 3 hours lecture; 3 semester hours.
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3.00 Credits
Introduction to applied multivariate techniques for data analysis. Topics include principal components, cluster analysis, MANOVA and other methods based on the multivariate Gaussian distribution, discriminant analysis, classification with nearest neighbors.Prerequisites: MATH335 or MATH323. 3 hours lecture; 3 semester hours.
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3.00 Credits
An introduction to stochastic models applicable to problems in engineering, physical science, economics, and operations research. Markov chains in discrete and continuous time, Poisson processes, and topics in queuing, reliability, and renewal theory. Prerequisite: MATH334. 3 hours lecture, 3 semester hours.
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3.00 Credits
This course is designed to facilitate students' learning of parallel programming techniques to efficiently simulate various complex processes modeled by mathematical equations usin multiple and multi-core processors. Emphasis will be placed on implementation of various scientific computing algorithms in FORTRAN 90 and its variants using MPI and OpenMP. Prerequisite: CSCI/MATH407. 3 hours lecture; 3 semester hours.
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3.00 Credits
Data structures suitable for the representation of structures, maps, three-dimensional plots. Algorithms required for windowing, color plots, hidden surface and line, perspective drawings. Survey of graphics software and hardware systems. Prerequisite: CSCI262. 3 hours lecture, 3 semester hours.
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3.00 Credits
The complex plane. Analytic functions, harmonic functions. Mapping by elementary functions. Complex integration, power series, calculus of residues. Conformal mapping. Prerequisite: MATH225 or MATH235. 3 hours lecture, 3 semester hours.
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3.00 Credits
Linear partial differential equations, with emphasis on the classical second-order equations: wave equation, heat equation, Laplace's equation. Separation of variables, Fourier methods, Sturm-Liouville problems. Prerequisite: MATH225 or MATH235. 3 hours lecture; 3 semester hours.
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