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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.

Basic Enrollment Requirements: Unofficial Transcript – High School Diploma or current high school transcript (for high school students only in applicable classes), Bachelor’s Degree, or progress towards a Bachelor’s Degree + 3.0 GPA.

Refund Policy: The refund policy for Courses at Tufts offerings is dependent on the course length. Please refer to the section details to confirm any exceptions to the standard refund policy. The refund policies are viewable here: https://universitycollege.tufts.edu/policies#Refunds 

Remission Eligible: Yes; first day of term; all university policies apply.

Affiliated With:

  • School of Arts and Sciences