The B.S. in mathematics degree with an emphasis in data science program provides a sufficient background in mathematics, statistics, and to some extent, computer science, to produce graduates who can work in areas requiring applied mathematical techniques and tools. This degree is structured to allow additional, optional, courses that enable the student to focus on a variety of further areas of interest.

Degree Requirements

The following is a brief summary of degree requirements. For complete information and restrictions, please consult the University of Missouri-St. Louis Bulletin appropriate for you.

**I.** All general education requirements of the University. Courses in the major may be used to meet the university’s general education breadth of study requirement in natural sciences and mathematics.

**II. The following course work in the Department of Mathematics and Statistics is required.** (Must be completed with a grade of C- or higher)

Courses | Required Hours | |
---|---|---|

CMP SCI 1250 |
Introduction to Computing | 3 |

CMP SCI 2250 |
Programming and Data Structures | 3 |

MATH 1320 |
Introduction to Probability and Statistics | 3 |

MATH 1800 |
Analytic Geometry and Calculus I | 5 |

MATH 1900 |
Analytic Geometry and Calculus II | 5 |

MATH 2000 |
Analytic Geometry and Calculus III | 5 |

MATH 2020 |
Introduction to Differential Equations | 3 |

MATH 2450 |
Elementary Linear Algebra | 3 |

MATH 3250 |
Foundations of Mathematics | 3 |

MATH 4100 |
Real Analysis I | 3 |

Total Hours |
36 |

Courses | |
---|---|

MATH 3320 |
Applied Statistics |

MATH 4080 |
Introduction to Scientific Computation |

MATH 4090 |
Introduction to High-dimensional Data Analysis |

MATH 4220 |
Bayesian Statistical Methods |

MATH 4225 |
Introduction to Statistical Computing |

MATH 4260 |
Introduction to Stochastic Processes |

MATH 4450 |
Linear Algebra |