Fall 2016


Stochastic Processes in Finance II

This is the second of a two-semester sequence that develops basic probability concepts and models for working with financial markets and derivative securities. Continuous-time parameter stochastic processes are emphasized in this course. Mathematical concepts are introduced as needed.

Algebra I

Graduate level linear and abstract algebra including groups, rings, modules, and fields. (1st of two courses)

Graph Theory

Fundamentals, connectivity, matchings, colorings, extremal problems, Ramsey theory, planar graphs, perfect graphs. Applications to operations research and the design of efficient algorithms.

Survey of Calculus

Functions, the derivative, applications of the derivative, techniques of differentiation, integration, applications of integration to probability and statistics, multidimensional calculus.

Finite Mathematics

Linear equations, matrices, linear programming, sets and counting, probability and statistics.

Honors Differential Equations

The topics covered parallel those of MATH 2552 with a somewhat more intensive and rigorous treatment.

Differential Equations

Methods for obtaining numerical and analytic solutions of elementary differential equations. Applications are also discussed with an emphasis on modeling.

Multivariable Calculus

Linear approximation and Taylor’s theorems, Lagrange multiples and constrained optimization, multiple integration and vector analysis including the theorems of Green, Gauss, and Stokes.

Introduction to Multivariable Calculus

An introduction to multivariable calculus through vectors in 3D, curves, functions of several variables, partial derivatives, min/max problems, multiple integration. Vector Calculus not covered.

Linear Algebra with Abstract Vector Spaces

This is an intensive course on linear algebra, taught at a sophisticated and abstract level.


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