Mathematics BS, Data Science Emphasis

Program Overview

The Mathematics B.S. with an emphasis in Data Science provides a strong foundation in mathematics, statistics, and computer science. Students will develop skills in data analysis, modeling, and optimization, preparing them for careers in data science, machine learning, and related fields. The program includes core courses in calculus, linear algebra, and probability and statistics, as well as emphasis area courses in data analysis, optimization, and statistical methods. Students can choose from a variety of elective courses to tailor their program to their interests and career goals.

Program Outline

Outline:

The Mathematics B.S. program with an emphasis in Data Science requires the following core courses:

• CMP SCI 1250 Introduction to Computing 13
• 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
OR
• CMP SCI 3130 Design and Analysis of Algorithms
• MATH 4100 Real Analysis I 23
In addition to the core requirements, students must complete the following emphasis area requirements: CMP SCI 2250 Programming and Data Structures 3 MATH 4005 Exploratory Data Analysis with R 3 MATH 4070 Introduction to Nonlinear Optimization 3 MATH 4200 Mathematical Statistics I 3 MATH 4210 Mathematical Statistics II 3 MATH 4250 Introduction to Statistical Methods in Learning and Modeling 3 Students can choose two courses from the following list:
• 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
• MATH 4750 Introduction to Mathematics of Artificial Neural Networks
and two additional courses in mathematics, statistics, or computer science numbered above 4000.