Applied Mathematics Major (B.S.)

This degree prepares students for careers in science, engineering, and industry by giving students broad exposure to both theoretical and computational models of physical systems in the physical, natural, and social sciences.

Degree Requirements

Minimum Credit Requirement: 128 credits
Minimum Residency Requirement: 32 credits must be taken at UNH
Minimum GPA: 2.0 required for conferral*
Core Curriculum Required: Discovery & Writing Program Requirements
Foreign Language Requirement: No

All Major, Option and Elective Requirements as indicated.
*Major GPA requirements as indicated.

Major Requirements

In all courses used to satisfy the requirements for its major programs, the Department of Mathematics and Statistics requires that a student earn a grade of C- or better and have an overall grade-point average of at least 2.00 in these courses.

Required MATH Courses
MATH 425Calculus I4
MATH 426Calculus II4
MATH 445Mathematics and Applications with MATLAB4
or IAM 550 Introduction to Engineering Computing
MATH 527Differential Equations with Linear Algebra 14
MATH 528Multidimensional Calculus 14
MATH 531Mathematical Proof4
MATH 545Introduction to Linear Algebra 24
or MATH 645 Linear Algebra for Applications
MATH 644Statistics for Engineers and Scientists4
MATH 647Complex Analysis for Applications4
or MATH 788 Complex Analysis
MATH 745Foundations of Applied Mathematics I4
MATH 753Introduction to Numerical Methods I4
MATH 757Mathematical Optimization for Applications4
Capstone: Select one of the following
MATH 797Senior Seminar4
MATH 798Senior Project4
MATH 799Senior Thesis2 or 4
Select TWO of the following electives
MATH 746Foundations of Applied Mathematics II4
MATH 747Introduction to Nonlinear Dynamics and Chaos4
MATH 767One-Dimensional Real Analysis4
One approved CEPS course at the 700-level, selected in consultation with the academic advisor4
Other Required Courses
PHYS 407General Physics I4
PHYS 408General Physics II4
CS 415
CS 416
Introduction to Computer Science I
and Introduction to Computer Science II
or CS 414
CS 417
From Problems to Algorithms to Programs
and From Programs to Computer Science
Total Credits90-92

The full Linearity sequence, MATH 525 & MATH 526, may be used to replace the MATH 527, MATH 528, and MATH 545 / MATH 645 requirements.


MATH 525 may be used to replace the MATH 545 or MATH 645 requirement.

Plan of Study Grid
First Year
MATH 425 Calculus I 4
CS 415 Introduction to Computer Science I 4
Discovery Course 4
Inquiry Course 4
MATH 400 Freshman Seminar 1
MATH 426 Calculus II 4
CS 416 Introduction to Computer Science II 4
ENGL 401 First-Year Writing 4
Discovery Course 4
Second Year
MATH 445
Mathematics and Applications with MATLAB
or Introduction to Engineering Computing
MATH 527 Differential Equations with Linear Algebra 4
PHYS 407 General Physics I 4
Discovery Course 4
MATH 528 Multidimensional Calculus 4
MATH 531 Mathematical Proof 4
PHYS 408 General Physics II 4
Discovery Course 4
Third Year
MATH 545
Introduction to Linear Algebra
or Linear Algebra for Applications
MATH 644 Statistics for Engineers and Scientists 4
MATH 753 Introduction to Numerical Methods I 4
Discovery Course 4
MATH 757 Mathematical Optimization for Applications 4
CEPS 700-level elective 4
Discovery Course 4
Elective 4
Fourth Year
MATH 745 Foundations of Applied Mathematics I 4
Writing Intensive Course 4
Elective 4
Elective 4
MATH 647
Complex Analysis for Applications
or Complex Analysis
MATH 797
Senior Seminar
or Senior Project
or Senior Thesis
Writing Intensive Course 4
Elective 4
 Total Credits129
  • Students recognize common mathematical notations and operations used in mathematics, science and engineering.
  • Students can recognize and classify a variety of mathematical models including differential equations, linear and nonlinear systems of algebraic equations, and common probability distributions.
  • Students have developed a working knowledge (including notation, terminology, foundational principles of the discipline, and standard mathematical models within the discipline) in at least one discipline outside of mathematics.
  • Students are able to extract useful knowledge, both quantitative and qualitative, from mathematical models and can apply that knowledge to the relevant discipline.