Applied Mathematics Major: Computation Option (B.S.)

https://ceps.unh.edu/mathematics-statistics/program/bs/applied-mathematics-computation-option

This degree program prepares students for employment and/or graduate study in a variety of fields and research specializations in which mathematics plays a critical role in the solution of important scientific and technological problems.

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.

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 644Statistics for Engineers and Scientists 24
MATH 645Linear Algebra for Applications 14
MATH 753Introduction to Numerical Methods I4
PHYS 407General Physics I4
Capstone: Select one of the following
MATH 797Senior Seminar4
MATH 798Senior Project4
MATH 799Senior Thesis2 or 4
Total Credits50-52
1

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

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

2

Applied Mathematics: Economics Option students must take MATH 539 Introduction to Statistical Analysis.

Computation Option Requirements

PHYS 408General Physics II4
MATH 647Complex Analysis for Applications4
MATH 745Foundations of Applied Mathematics I4
CS 415
CS 416
Introduction to Computer Science I
and Introduction to Computer Science II
8
CS 420Foundations of Programming for Digital Systems4
CS 515Data Structures and Introduction to Algorithms4
CS 659Introduction to the Theory of Computation4
CS 758Algorithms4
IAM 751Introduction to High-Performance Computing4
Total Credits40
Plan of Study Grid
First Year
FallCredits
MATH 425 Calculus I 4
CS 415 Introduction to Computer Science I 4
Discovery Course 4
Inquiry Course 4
MATH 400 Freshman Seminar 1
 Credits17
Spring
MATH 426 Calculus II 4
MATH 445
Mathematics and Applications with MATLAB
or Introduction to Engineering Computing
4
CS 416 Introduction to Computer Science II 4
ENGL 401 First-Year Writing 4
 Credits16
Second Year
Fall
MATH 528 Multidimensional Calculus 4
MATH 531 Mathematical Proof 4
PHYS 407 General Physics I 4
CS 420 Foundations of Programming for Digital Systems 4
 Credits16
Spring
MATH 527 Differential Equations with Linear Algebra 4
MATH 644 Statistics for Engineers and Scientists 4
PHYS 408 General Physics II 4
CS 515 Data Structures and Introduction to Algorithms 4
 Credits16
Third Year
Fall
MATH 647 Complex Analysis for Applications 4
MATH 753 Introduction to Numerical Methods I 4
CS 659 Introduction to the Theory of Computation 4
Discovery Course 4
 Credits16
Spring
MATH 645 Linear Algebra for Applications 4
IAM 751 Introduction to High-Performance Computing 4
CS 758 Algorithms 4
Discovery Course 4
 Credits16
Fourth Year
Fall
MATH 745 Foundations of Applied Mathematics I 4
Discovery Course 4
Discovery Course 4
Writing Intensive Course 4
 Credits16
Spring
MATH 797
Senior Seminar
or Senior Project
or Senior Thesis
4
Discovery Course 4
Writing Intensive Course 4
Elective Course 4
 Credits16
 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.