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MATH 3070: Calculus IV
3.00 Credits
Webster University
This course studies calculus with more rigor and depth than in the usual calculus sequence. Prerequisite: MATH 3000.
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MATH 3110: Introduction to Abstract Mathematics
3.00 Credits
Webster University
Introduces monadic and general predicate calculus as a methodology for understanding and writing mathematical proofs. Prerequisite: MATH 1620.
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MATH 3130: Real Number System
3.00 Credits
Webster University
Studies the real number system: field properties, order properties, topological properties. Sequences of real numbers and their limits will be analyzed. Functions of real variables, especially continuous functions, will be studied. Prerequisite: MATH 1620.
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MATH 3160: Linear Algebra
3.00 Credits
Webster University
Linear algebra is concerned with vectors, matrices, and systems of linear equations and with functions called linear transformations. Linear algebra is one of the most important tools of applied mathematics. Some of the disciplines using linear algebra are economics, physics, biology, statistics, computer graphics, engineering, business, ecology, sociology, demography, and genetics. Prerequisite: MATH 3000 or may be taken concurrently.
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MATH 3200: Statistics
3.00 Credits
Webster University
Statistics is the science of analyzing data and arriving at reasonable and intelligent conclusions based upon that analysis. This course will acquaint students with the mathematical concepts of statistical analysis. Prerequisite: MATH 1610.
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MATH 3210: Data Mining Foundations
3.00 Credits
Webster University
This course explores the core concepts of data mining including the research methodology and process, data sources, messy data and data cleansing. It also examines algorithms in each of the main data mining groupings of classification, categorization, and association rules. The course emphasizes the use of data mining concepts in real-world applications with database components. Students will present their findings and recommendations in written and oral project reports. Prerequisite: MATH 1610 Calculus I
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MATH 3220: Data Mining Methods
3.00 Credits
Webster University
This course surveys the current techniques of problem solving using modern heuristics. It covers classic methods of optimization, including dynamic programming, the simplex method, and gradient techniques, as well as recent innovations such as simulated annealing, tabu search, and evolutionary computation. Besides exploring a compendium of specific techniques, this course also delves into the approaches of framing and attacking the issue of problem solving itself. Students will present their findings and recommendations in written and oral project reports. Prerequisite: MATH 1610 Calculus I
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MATH 3300: Introduction to Number Theory
3.00 Credits
Webster University
Studies elementary properties of integers, primes, congruencies, and arithmetic functions. Prerequisite: MATH 3000.
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MATH 3510: Vector Geometry
3.00 Credits
Webster University
This course studies geometry using vectors. Prerequisite: MATH 3000.
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MATH 3530: Modern Geometry
3.00 Credits
Webster University
Geometry is studied using post-Euclidean methods. Prerequisite: MATH 1620.
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MATH 3530 - Modern Geometry
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