Applied Mathematics, BS
Degree: Bachelor of Science (BS)
Major: Applied Mathematics
Program Overview
All undergraduate degrees in the Department of Mathematics, Applied Mathematics and Statistics are based on a four-course sequence in calculus and differential equations. The mathematics and applied mathematics degrees each require further mathematics courses in analysis and algebra. The statistics degrees each require a further statistics core. There are additional requirements particular to each degree program, including technical electives in the major. Each degree program requires a minimum of 120 credit hours.
The BS in Applied Mathematics prepares students to solve real-world problems using mathematical modeling, numerical methods, and computer simulations. Like the BS in Mathematics, the BS in Applied Mathematics requires a core of linear algebra and analysis, but additionally requires courses in computing and probability instead of abstract algebra and complex analysis. The technical electives for the BS in Applied Mathematics include offerings such as Partial Differential Equations, Mathematical Modeling, and Applied Probability. The degree provides a solid basis for graduate studies in applied mathematics and related areas where mathematical methods play a central role, and provides analytic and computational tools for successful work in applied research and industry.
Learning Outcomes
- Students will be able to know the fundamental concepts of linear algebra: Vector spaces, linear operators and matrices, four fundamental subspaces, matrix factorizations, and the solution theory of linear systems.
- Students will be able to correctly analyze the solvability of linear problems in practice, and be able to solve linear systems.
- Students will be able to know the fundamental concepts of calculus and classical mathematical analysis: Metric spaces, limits and convergence, continuity, and differential and integral calculus.
- Students will be able to demonstrate the capability of rigorous abstract thinking, and be able to set up a rigorous mathematical proof.
- Students will be able to know the key concepts of scientific computing: Accuracy, stability, computational complexity.
- Students will be able to know and able to use the key elements of scientific computing, including solving linear and non-linear equations, approximation, interpolation, numerical differentiation and quadrature rules.
- Students will be able to express a given problem in quantitative terms, and/or find the appropriate set of mathematical tools to tackle the problem, and/or be able to select and implement an algorithm that leads to the solution of the problem.
- Students will be able to communicate effectively the results to a non-expert in mathematics, and be able to put the work in the proper context.
Undergraduate Policies
For undergraduate policies and procedures, please review the Undergraduate Academics section of the General Bulletin.
Combined Bachelor's/Master's Programs
Undergraduate students may participate in accelerated programs toward graduate or professional degrees. For more information and details of the policies and procedures related to accelerated studies, please visit the Undergraduate Academics section of the General Bulletin.
Program Requirements
Students seeking to complete this major and degree program must meet the general requirements for bachelor's degrees and the Unified General Education Requirements. Students completing this program as a secondary major while completing another undergraduate degree program do not need to satisfy the school-specific requirements associated with this major.
The BS degree in applied mathematics requires at least 50 credit hours of coursework in mathematics and related subjects, and at least 17 credit hours in basic science.
| Code | Title | Credit Hours |
|---|---|---|
| Mathematics Requirements | ||
| MATH 121 | Calculus for Science and Engineering I | 4 |
| or MATH 123 | Calculus I | |
| MATH 122 | Calculus for Science and Engineering II | 4 |
| or MATH 124 | Calculus II | |
| MATH 223 | Calculus for Science and Engineering III | 3 |
| or MATH 227 | Calculus III | |
| MATH 224 | Elementary Differential Equations | 3 |
| or MATH 228 | Differential Equations | |
| MATH 307 | Linear Algebra | 3 |
| MATH 321 | Fundamentals of Analysis I | 3 |
| MATH 322 | Fundamentals of Analysis II | 3 |
| MATH 330 | Introduction to Scientific Computing | 3 |
| MATH 380 | Introduction to Probability | 3 |
| Choose one of the following: | 3 | |
| Introduction to Complex Analysis | ||
| Complex Analysis I | ||
| Non-Mathematics Requirements | ||
| PHYS 121 | General Physics I - Mechanics | 4 |
| PHYS 122 | General Physics II - Electricity and Magnetism | 4 |
| PHYS 221 | Introduction to Modern Physics | 3 |
| Choose one of the following sequences: | 6-8 | |
| Introduction to the Sun and Its Planets and Introduction to the Stars, Galaxies, and the Universe | ||
| Principles of Chemistry I and Principles of Chemistry II | ||
| Principles of Chemistry for Engineers and Chemistry of Materials | ||
| Physical Geology and Introduction to Oceanography | ||
| Physical Geology and Earth History: Time, Tectonics, Climate, and Life | ||
| Mathematics Electives | ||
| Choose three of the following: | 9 | |
| Applied Probability and Stochastic Processes for Biology | ||
| Mathematics and Brain | ||
| Introduction to Linear Partial Differential Equations | ||
| Mathematical Modeling | ||
| Mathematical Analysis of Biological Models | ||
| Computational Neuroscience | ||
| Introduction to Information Theory | ||
| Fourier Analysis and Applications | ||
| Introduction to Numerical Analysis I | ||
| Numerical Differential Equations | ||
| Numerical Solutions of Nonlinear Systems and Optimization | ||
| Ordinary Differential Equations | ||
| Bayesian Scientific Computing | ||
| Computational Inverse Problems | ||
| Mathematical Modeling | ||
| Mathematics of Data Mining and Pattern Recognition | ||
| Introduction to Partial Differential Equations | ||
| Numerical Methods for Partial Differential Equations | ||
| Computational Fluid Mechanics | ||
| Dynamical Models for Biology and Medicine | ||
| Introduction to Mathematical Image Processing and Computer Vision | ||
| Introduction to Stochastic Processes | ||
| Additional Electives | ||
| Three MATH or STAT courses a,b | 9 | |
| Total Credit Hours | 67-69 | |
- a
300 level or higher.
- b
With approval of the student's major advisor, courses from outside MATH or STAT may be chosen.