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Course Criteria
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1.50 Credits
Linear systems, interpolation, functional approximation, numeric differentiation and integration, and solutions to non-linear equations.
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1.50 Credits
Three dimensional geometry, directional derivatives, gradient, divergence, curl, maximum- minimum problems, multiple integrals, parametric surfaces and curves, and line integrals.
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1.50 Credits
Review of random variables, discrete and continuous distributions, expectation, conditional probability, and limit theorems. Introduction to the Poisson point process and Markov chains.
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1.50 Credits
Review of statistical estimation and hypothesis testing. Introduction to nonparametric methods, permutation tests, the bootstrap, and Bayesian statistics.
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1.50 Credits
Linear and nonlinear regression, logistic regression, analysis of variance, and generalized linear models.
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1.50 Credits
Principles of experimental design, randomization, blocking, factorial designs, repeated measures, and Latin squares.
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1.50 Credits
Classes, objects, instances, messages, methods, inheritance, interfaces, polymorphism, software life cycle, variables, expressions, data objects, control structures, strings, arrays, files, searching, sorting, applets, toolkits, threads, and graphical user interfaces.
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1.50 Credits
Abstract data types, stacks, queues, databases, priority queues, trees, linked hashing, balanced trees, self-organizing data structures, and advanced sorting.
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1.50 Credits
Computer representation and hardware, system programming, prototyping development, memory and data organization, communications and networking, human/computer interactions, and performance analysis and improvement.
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1.50 Credits
Software development processes and the software life cycle, software architecture and design, emphasizing object-oriented design, user interface design, validation and verification, testing methods, systems analysis and requirements definition, software management and personal issues.
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