# Computer Science-Mathematical Sciences (Combined Major)

The purpose of the combined program is to provide a thorough background in both allied disciplines and to inculcate a deeper understanding of their goals and methods. A student must complete 60 credits in the two disciplines:

- 30 of these credits in Computer Science courses and
- 30 of these credits in Mathematical Sciences courses.

Each student plans a program in consultation with a Computer Science and a Mathematical Sciences advisor. Students planning to attend graduate school in computer science or the mathematical sciences should consult with their respective advisors.

## Bachelor of Science - Computer Science-Mathematical Science

### College of Humanities & Sciences

**Degree Specific Credits:** 73-74

**Required Cumulative GPA:** 2.0

### Catalog Year: 2018-2019

## General Education Requirements

Information regarding these requirements can be found in the General Education Section of the catalog.

## Summary

Code | Title | Hours |
---|---|---|

Mathematical Science | 31 | |

Computer Science | 30 | |

Science Requirement | 9-10 | |

Biology Sequence Option | ||

Chemistry Sequence Option | ||

Physics Sequence Option | ||

Public Speaking Requirement | 3 | |

Total Hours | 73-74 |

### Mathematical Sciences

**Rule:** Complete the following subcategories. 31 total credits required.

#### Mathematical Sciences Core

Code | Title | Hours |
---|---|---|

Complete all of the following courses: | ||

M 171 | Calculus I | 4 |

or M 181 | Honors Calculus I | |

M 172 | Calculus II | 4 |

or M 182 | Honors Calculus II | |

M 221 | Introduction to Linear Algebra | 4 |

M 273 | Multivariable Calculus | 4 |

M 307 | Introduction to Abstract Mathematics | 3 |

or M 225 | Introduction to Discrete Mathematics | |

Total Hours | 19 |

Minimum Required Grade: C-

#### Mathematical Sciences Electives

**Note:** The combined nine credits of Computer Science Electives and twelve credits of Mathematical Sciences Electives must include at least three 3– or 4–credit courses numbered 400 or above, with at least one chosen from each department (not including M 429 and STAT 451, STAT 452).

Code | Title | Hours |
---|---|---|

Complete 12 credits of the following courses: | 12 | |

Ordinary Differential Equations and Systems | ||

Discrete Mathematics | ||

Number Theory | ||

Discrete Optimization | ||

Linear Optimization | ||

Advanced Calculus I | ||

Partial Differential Equations | ||

Deterministic Models | ||

History of Mathematics | ||

Abstract Algebra I | ||

Abstract Algebra II | ||

Euclidean and NonEuclidean Geometry | ||

Numerical Analysis | ||

Statistical, Dynamical, and Computational Modeling | ||

Data Science Analytics | ||

Theoretical Basics of Big Data Analytics and Real Time Computation Algorithms | ||

Introduction to Complex Analysis | ||

Introduction to Real Analysis | ||

Graph Theory | ||

Introduction to Probability and Statistics | ||

Probability Theory | ||

Mathematical Statistics | ||

Statistical Methods I | ||

Statistical Methods II | ||

Total Hours | 12 |

Minimum Required Grade: C-

### Computer Science

**Rule:** Complete the following subcategories. 30 total credits required.

#### Computer Science Core

Code | Title | Hours |
---|---|---|

Complete all of the following courses: | ||

CSCI 106 | Careers in Computer Science | 1 |

CSCI 135 | Fund of Computer Science I | 3 |

CSCI 136 | Fund of Computer Science II | 3 |

CSCI 205 | Programming Languages w/ C/C++ | 4 |

CSCI 232 | Data Structures and Algorithms | 4 |

CSCI 332 | Design/Analysis of Algorithms | 3 |

CSCI 361 | Computer Architecture | 3 |

Total Hours | 21 |

Minimum Required Grade: C-

*Computer Science Electives*

**Note:**

- A total of at most three of the nine credits of Computer Science Electives may be in CSCI 398 or CSCI 498.
- The combined nine credits of Computer Science Electives and twelve credits of Mathematical Sciences Electives must include at least three 3– or 4–credit courses numbered 400 or above, with at least one chosen from each department (not including M 429 and STAT 451, STAT 452).

Code | Title | Hours |
---|---|---|

Complete 9 credits of the following courses: | 9 | |

Computers, Ethics, and Society | ||

Software Science | ||

Database Design | ||

Research | ||

Special Topics | ||

Seminar | ||

Internship | ||

Advanced Web Programming | ||

Game and Mobile App | ||

Adv Prgrmng Theory/Practice I | ||

Adv Prgrmng Theory/Practice II | ||

Computer Graphics Programming | ||

User Interface Design | ||

Data Visualization | ||

Artificial Intelligence | ||

Machine Learning | ||

Pattern Recognition | ||

Computational Biology | ||

Operating Systems | ||

Applications of Mining Big Data | ||

Networks | ||

Simulation | ||

Applied Parallel Computing Techniques | ||

Research | ||

Special Topics | ||

Seminar | ||

Internship | ||

Senior Thesis/Capstone | ||

Total Hours | 9 |

Minimum Required Grade: C-

### Science Requirement

**Rule:** Complete 1 of the following subcategories. 9-10 total credits required.

#### Biology Sequence Option

Code | Title | Hours |
---|---|---|

Complete all of the following courses: | ||

BIOB 160N | Principles of Living Systems | 3 |

BIOB 161N | Prncpls of Living Systems Lab | 1 |

BIOB 170N | Princpls Biological Diversity | 3 |

BIOB 171N | Princpls Biological Dvrsty Lab | 2 |

Total Hours | 9 |

Minimum Required Grade: C-

#### Chemistry Sequence Option

Code | Title | Hours |
---|---|---|

Complete all of the following courses: | ||

CHMY 141N & CHMY 142N | College Chemistry I and College Chemistry I Lab | 5 |

CHMY 143N & CHMY 144N | College Chemistry II and College Chemistry II Lab | 5 |

Total Hours | 10 |

Minimum Required Grade: C-

#### Physics Sequence Option

Code | Title | Hours |
---|---|---|

Complete all of the following courses: | ||

PHSX 215N | Fund of Physics w/Calc I | 4 |

PHSX 216N | Physics Laboratory I w/Calc | 1 |

PHSX 217N | Fund of Physics w/Calc II | 4 |

PHSX 218N | Physics Laboratory II w/Calc | 1 |

Total Hours | 10 |

Minimum Required Grade: C-

### Public Speaking Requirement

Code | Title | Hours |
---|---|---|

Complete 1 of the following courses: | 3 | |

Introduction to Public Speaking | ||

Argumentation | ||

Total Hours | 3 |

Minimum Required Grade: C-

### Suggested Curricula

**Note:** Students are encouraged to choose their Computer Science and Mathematical Sciences Electives according to one of the following curricula; these tracks are suggestions only and, as such, optional. Note that the suggested curricula do not include an advanced College Writing Course.

#### Applied Math–Scientific Programming

Code | Title | Hours |
---|---|---|

M 311 | Ordinary Differential Equations and Systems | 3 |

M 412 | Partial Differential Equations | 3 |

M 414 | Deterministic Models | 3 |

Select one of the following: | 3-4 | |

Advanced Calculus I | ||

Numerical Analysis | ||

Introduction to Complex Analysis | ||

Introduction to Real Analysis | ||

Introduction to Probability and Statistics | ||

Select three of the following: | 9 | |

Computer Graphics Programming | ||

Data Visualization | ||

Operating Systems | ||

Simulation | ||

Total Hours | 21-22 |

#### Combinatorics and Optimization–Artificial Intelligence

Code | Title | Hours |
---|---|---|

M 361 | Discrete Optimization | 3 |

M 362 | Linear Optimization | 3 |

Select two of the following: | 6 | |

Discrete Mathematics | ||

Deterministic Models | ||

Graph Theory | ||

Introduction to Probability and Statistics | ||

CSCI 446 | Artificial Intelligence | 3 |

CSCI 447 | Machine Learning | 3 |

CSCI 460 | Operating Systems | 3 |

Total Hours | 21 |

#### Data Science (Big Data Analytics)

Code | Title | Hours |
---|---|---|

M 461 | Data Science Analytics | 3 |

M 462 | Theoretical Basics of Big Data Analytics and Real Time Computation Algorithms | 3 |

STAT 341 | Introduction to Probability and Statistics | 3 |

STAT 451 | Statistical Methods I | 3 |

STAT 452 | Statistical Methods II | 3 |

Select three of the following: | 9 | |

Data Visualization | ||

Machine Learning | ||

Pattern Recognition | ||

Applications of Mining Big Data | ||

Applied Parallel Computing Techniques | ||

Total Hours | 24 |

#### Statistics–Machine Learning

Code | Title | Hours |
---|---|---|

STAT 341 | Introduction to Probability and Statistics | 3 |

STAT 421 | Probability Theory | 3 |

Select two of the following: | 6 | |

Discrete Mathematics | ||

Linear Optimization | ||

Graph Theory | ||

Mathematical Statistics | ||

Select three of the following: | 9 | |

Database Design | ||

Data Visualization | ||

Artificial Intelligence | ||

Machine Learning | ||

Computational Biology | ||

Total Hours | 21 |

#### Algebra–Analysis

Code | Title | Hours |
---|---|---|

M 381 | Advanced Calculus I | 3 |

M 431 | Abstract Algebra I | 4 |

Select two of the following: | 7-8 | |

Number Theory | ||

Abstract Algebra II | ||

Introduction to Complex Analysis | ||

Introduction to Real Analysis | ||

CSCI 426 | Adv Prgrmng Theory/Practice I | 3 |

CSCI 460 | Operating Systems | 3 |

CSCI Elective | 3 | |

Total Hours | 23-24 |