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Course Description

A survey of major techniques in the use of mathematics to model physical, biological, economic, and other systems; topics may include derivative-based optimization and sensitivity analysis, linear programming, graph algorithms, probabilistic modeling, Monte-Carlo methods, difference equations, and statistical data fitting. This course includes an introduction to computing using a high-level programming language, and studies the transformation of mathematical objects into computational algorithms. Prerequisites: (1) MATH 34 , 36, or 39, and (2) Math 70 or 72, or permission of instructor.Recommendations: MATH 34, MATH 36 or MATH 39, or consent.

Affiliated With:

  • School of Arts & Sciences