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Course Demos: Mathematics

The following lecture example gives you a chance to see the format of the Mathematics courses offered by the University of Illinois Engineering Online program.

The course demos use Windows Media Technology and must be viewed with Internet Explorer 5.0 or later along with Windows Media Player using a Windows operating system on your computer.

 

MATH 488: Mathematical Methods in Engineering

  • View MATH 488 Course Introduction
  • Instructor: Anthony Peressini
  • Course Description: The primary objective of this course is to provide an introduction to a variety of methods in applied mathematics that are useful in engineering and science by using a problem solving approach. The content objectives include the following general topic areas: applied linear algebra and systems of linear and non-linear differential equations; orthogonal series methods including Fourier and Bessel series; the separation of variables method for boundary value problems involving partial differential equations; and discrete and continuous Fourier transform methods.
  • Prerequisites: Engineering calculus and some familiarity with elementary differential equations and matrices.

MATH 415: Linear Algebra

  • Instructors: Debra Woods and Bruce Carpenter
  • Course Description: This course provides a thorough introduction to matrix theory through the visual eyes of interactive Mathematica computer graphics and calculations. It includes dot product, cross product, and vector algebra; perpendicular frames; matrix action; stretching, flipping, and shearing; Matrix Maker; SVD analysis; rank of a matrix; subspaces, dimension, and linear independence; eigenvalues and eigenvectors; and round off and conditioning. Credit for this course is not applicable toward the MSME degree.
  • Prerequisites: A third-level course in calculus, including vector analysis.

MATH 461: Probability Theory I

  • Instructors: Debra Woods and Bruce Carpenter
  • Course Description: This course is an introduction to mathematical probability. Topics include calculus of probability, combinatorial analysis, random variables, expectation, distribution and moment-generating functions, and central limit theorem.
  • Prerequisites: A course in calculus and a course in advanced calculus.