# 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.

#### Graduation 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.

## Major Requirements

Code | Title | Credits |
---|---|---|

MATH 425 | Calculus I | 4 |

MATH 426 | Calculus II | 4 |

MATH 445 | Mathematics and Applications with MATLAB | 4 |

or IAM 550 | Introduction to Engineering Computing | |

MATH 527 | Differential Equations with Linear Algebra ^{1} | 4 |

MATH 528 | Multidimensional Calculus ^{1} | 4 |

MATH 531 | Mathematical Proof | 4 |

MATH 644 | Statistics for Engineers and Scientists ^{2} | 4 |

MATH 645 | Linear Algebra for Applications ^{1} | 4 |

MATH 753 | Introduction to Numerical Methods I | 4 |

PHYS 407 | General Physics I | 4 |

Capstone: Select one of the following | ||

MATH 797 | Senior Seminar | 4 |

MATH 798 | Senior Project | 4 |

MATH 799 | Senior Thesis | 2 or 4 |

Total Credits | 50-52 |

^{1} | MATH 525 Linearity I MATH 525 & MATH 526, Linearity, |

^{2} | Applied Mathematics: Economics Option students take MATH 539 Introduction to Statistical Analysis. |

## Computation Option Requirements

Code | Title | Credits |
---|---|---|

PHYS 408 | General Physics II | 4 |

MATH 647 | Complex Analysis for Applications | 4 |

MATH 745 | Foundations of Applied Mathematics I | 4 |

CS 414 & CS 417 | From Problems to Algorithms to Programs and From Programs to Computer Science | 8 |

or CS 415 & CS 416 | Introduction to Computer Science I and Introduction to Computer Science II | |

CS 515 | Data Structures and Introduction to Algorithms | 4 |

CS 659 | Introduction to the Theory of Computation | 4 |

CS 758 | Algorithms | 4 |

IAM 751 | Introduction to High-Performance Computing | 4 |

Total Credits | 36 |

First Year | ||
---|---|---|

Fall | Credits | |

MATH 425 | Calculus I | 4 |

CS 415 | Introduction to Computer Science I | 4 |

Discovery Course | 4 | |

Inquiry Course | 4 | |

MATH 400 | Freshman Seminar | 1 |

Credits | 17 | |

Spring | ||

MATH 426 | Calculus II | 4 |

MATH 445 | Mathematics and Applications with MATLAB | 4 |

CS 416 | Introduction to Computer Science II | 4 |

ENGL 401 | First-Year Writing | 4 |

Credits | 16 | |

Second Year | ||

Fall | ||

MATH 528 | Multidimensional Calculus | 4 |

MATH 531 | Mathematical Proof | 4 |

PHYS 407 | General Physics I | 4 |

CS 515 | Data Structures and Introduction to Algorithms | 4 |

Credits | 16 | |

Spring | ||

MATH 527 | Differential Equations with Linear Algebra | 4 |

MATH 539 | Introduction to Statistical Analysis | 4 |

PHYS 408 | General Physics II | 4 |

CS 659 | Introduction to the Theory of Computation | 4 |

Credits | 16 | |

Third Year | ||

Fall | ||

MATH 647 | Complex Analysis for Applications | 4 |

MATH 753 | Introduction to Numerical Methods I | 4 |

Discovery Course | 4 | |

CS 758 | Algorithms | 4 |

Credits | 16 | |

Spring | ||

MATH 645 | Linear Algebra for Applications | 4 |

Discovery Course | 4 | |

Discovery Course | 4 | |

IAM 751 | Introduction to High-Performance Computing | 4 |

Credits | 16 | |

Fourth Year | ||

Fall | ||

MATH 745 | Foundations of Applied Mathematics I | 4 |

Discovery Course | 4 | |

Writing Intensive Course | 4 | |

Elective Course | 4 | |

Credits | 16 | |

Spring | ||

Capstone: | 4 | |

Senior Seminar or Senior Project or Senior Thesis |
||

Discovery Course | 4 | |

Writing Intensive Course | 4 | |

Elective Course | 4 | |

Credits | 16 | |

Total Credits | 129 |

- 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.