Detailed Course Information |
Fall 2019
Apr 20,2024 |
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 | Select the desired Level or Schedule Type to find available classes for the course. |
| MATH 390 - ADVANCED TOPICS |
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The descriptions and topics of this course vary from semester-to-semester, as well as from instructor-to-instructor. Prerequisite: varies with the topic offered.
MATH 390 GRAPH THEORY. This course will provide a friendly introduction to graph theory. The primary focus of this class is to highlight the importance of graph theory in modern mathematics. Topics that underscore its utility include the basic properties of graphs, invariants of graphs, common families of graphs, adjacency matrix of a graph and its properties, colorings, connectivity, trees, forests and spanning trees.
MATH 390 LINEAR OPTIMIZATION. Linear Optimization is concerned with methods to allocate limited resources in an optimal way. Linear constraints are imposed on variables representing those resources. Among the variable values satisfying the restrictions, those that maximize or minimize a linear function of the unknowns are looked for. The Simplex Method, an algorithm to solve linear programs will be discussed. Several applications of interest for mathematics or computer science students will be presented: production processes, allocation of personnel and other scheduling problems, transportation problems, diet problems, among others.
MATH 390 MATHEMATICAL MODELING. This course is designed to introduce students to fundamental concepts and methods of mathematical modeling. We will study many model types, and learn techniques to construct and analyze appropriate models for a variety of applications. We will additionally build students' understanding of the general model-building process and develop a strong foundation with which students can confidently tackle real-world, open-ended problems. Topics may include discrete and continuous dynamical systems, proportionality and geometric similarity models, fitting models to data, simulations, probabilistic modeling, decision theory, or network science.
PARTIAL DIFFERENTIAL EQUATIONS: This is an introduction to partial differential equations that will cover first-order equations, linear second-order equations, separation of variables, solutions by series expansions, and boundary value problems. There will be some emphasis on equations related to physics, such as the heat equation and wave equation.
FALL 2024 MATH 39001 CRN 41478
In today's interconnected world, networks are everywhere, such as social, communication, and transportation networks, the Web, biological systems. Despite their diversity, all these networks share a common underlying structure: a complex system comprising interconnected components or entities. Utilizing the concept of networks provides a versatile framework for investigating and understanding these connected systems, which may provide insights in many contexts.
In this course, students explore a variety of real-world networks and how they help us understand the complex patterns and connected systems that shape our lives. Students will gain practical skills in utilizing computer-based tools for network analysis and modeling, along with acquiring a comprehensive understanding of the fundamental principles and theories. Upon successfully completing the course, students will have developed a solid foundation in network science, enabling them to appreciate the interconnected nature of the world around them and apply network analysis techniques to address complex problems.
0.000 TO 4.000 Credit hours 0.000 TO 4.000 Lecture hours Levels: Undergraduate Schedule Types: Hybrid, Lecture, Online Course Mathematics Department Restrictions: Must be enrolled in one of the following Levels: Undergraduate Prerequisites: FOR MATH 390 General Requirements: ( Course or Test: MATH 237 Minimum Grade of D May not be taken concurrently. ) or ( Course or Test: MATH 205 Minimum Grade of D May not be taken concurrently. ) and ( Course or Test: CMPS 147 Minimum Grade of D May not be taken concurrently. ) |
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