Courses

This course offers all of the Algebra with Applications curriculum with the addition of remedial material. This course is 3 credit hours, but meets 5 days per week. The S-section is intended for students with math placement 0.

This course provides an introduction to algorithm design and analysis, computational complexity, and NP-completeness theory.

Students focus on how to design and analyze computing algorithms with emphasis asymptotic analysis, recurrences and divide-and-conquer algorithms, greedy algorithms. Computational complexity theory and computability will also be

Syntax and data structures, algorithm development, and data plotting using currently relevant technical computing programing language(s). Prior knowledge of programming is not required, but the course is appropriate for students with prior programming experience. Prerequisite(s) with concurrency: MATH 125 or MATH 145

Fundamental aspects of algorithmic algebra. Noetherian rings. Theory of Groebner bases. Hilbert Nullstellensatz. Elimination theory. Applications to graph theory and algebraic geometry. 2188 Mathematics - MATH

Modules. Groebner bases for modules and syzygy computations. Improved Buchberger's algorithm. Computation of Ext. Groebner bases over rings. Primary decomposition of ideals. Dimension theory.

Best practices for the procedural generation of geometry, visual effects, and dynamics; process of creating geometry procedurally, how to create simple dynamic effects such as cloth and destruction simulations, and the fundamentals of creating visual effects such as explosions, smoke, and other fluids.

Theory and algorithms for solving computational problems in graphs and hypergraphs. The topics may include minimum transversals, maximum matchings, trees and bipartite graphs, chordal graphs, planar graphs and graph coloring, hypertrees, chordal hypergraphs, planar hypergraphs and hypergraph coloring, colorability, perfection, and chromatic spectrum.

Theory and algorithms for solving computational problems in graphs and hypergraphs. The topics may include minimum transversals, maximum matchings, trees and bipartite graphs, chordal graphs, planar graphs and graph coloring, hypertrees, chordal hypergraphs, planar hypergraphs and hypergraph coloring, colorability, perfection, and chromatic spectrum. Prerequisite(s): MTH 2220, MTH 4420, or MTH 5520, or permission of the instructor

This course covers classic algorithms in computer science and their applications. Emphasis is on algorithm design, algorithm analysis, problem formulation, and problem solving. Topics include advanced tree and graph algorithms, advanced sorting and searching algorithms, greedy algorithms, dynamic programming, string processing algorithms, and algorithm complexity (time and memory).