Professional Applied and Computational Mathematics (M.S.)
Admission Requirements
- Bachelor’s degree with a minimum cumulative GPA of 3.0 (4.0 scale) in the last 60 credit hours.
- If minimum requirements are not met, the graduate faculty may grant an applicant conditional admission to the program as a premajor if the applicant has a minimum cumulative GPA of 2.5 (4.0 scale) in the last 60 credit hours. If accepted to the premajor, the applicant must obtain a 3.0 or higher in the first semester and then reapply to the major (no additional application fees are required).
- The following mathematics courses completed: Single and Multivariable Calculus; Differential Equations; Linear Algebra; Discrete Mathematics; Calculus-based Probability; Calculus-based Statistics.
- Students must demonstrate knowledge of a standard programming language such as C++, Java, Fortran, Maple, or Mathematica.
- An interview with PACM faculty. In addition, all applicants should review the Admission to Graduate School section.
Program Requirements
| Code | Title | Credit Hours |
|---|---|---|
| Required Analytical Mathematical Modeling (9 credit hours) | 9 | |
| Select any nine credit hours from the following: | ||
| MATHEMATICAL MODELING AND APPLICATIONS I (1) | ||
| MATHEMATICAL MODELING AND APPLICATIONS II (1) | ||
| MATHEMATICAL MODELING AND APPLICATIONS III (1) | ||
| CONTINUOUS FOUNDATIONS OF APPLIED MATHEMATICS FROM A PROBLEM SOLVING PERSPECTIVE (1) | ||
| DISCRETE FOUNDATIONS OF APPLIED MATHEMATICS FROM A PROBLEM SOLVING PERSPECTIVE (1) | ||
| COMPUTATIONAL FOUNDATIONS OF APPLIED MATHEMATICS FROM A PROBLEM SOLVING PERSPECTIVE (1) | ||
| SPREADSHEETS AND DATABASES FOR MATH (1) | ||
| STATISTICAL AND DATA ANALYSIS SOFTWARE FOR MATH AND SCIENCE PROFESSIONALS (1) | ||
| OPTIMIZATION OF DISCRETE MODELS (1) | ||
| EMPIRICAL MODEL BUILDING (1) | ||
| MODELING CHANGE WITH DYNAMICAL SYSTEMS (1) | ||
| NUMERICAL LINEAR ALGEBRA (1) | ||
| EIGENVALUE PROBLEMS (1) | ||
| NUMERICAL CALCULUS (1) | ||
| Required Statistical Data Analysis (9-11 credit hours) | 9-11 | |
| LINEAR REGRESSION AND CORRELATION (1) | ||
| DESIGN AND ANALYSIS OF EXPERIMENTS (1) | ||
| NONPARAMETRIC STATISTICS (1) | ||
| RANDOM WALKS AND BROWNIAN MOTION (1) | ||
| MARKOV CHAINS (1) | ||
| CONTINUOUS-TIME STOCHASTIC PROCESSES (1) | ||
| MARKOV CHAIN MODELS IN CREDIT RISK MANAGEMENT (1) | ||
| MATHEMATICS OF FINANCE I: MODELING, ANALYSIS AND NUMERICAL METHODS (1) | ||
| MATHEMATICS OF FINANANCE II: MODELING, ANALYSIS AND NUMERICAL METHODS (1) | ||
| LOGISTIC REGRESSION (1) | ||
| SURVIVAL ANALYSIS (1) | ||
| TIME SERIES ANALYSIS AND FORECASTING (1) | ||
| Required Business Intelligence and Data Analytics (9 credit hours) | 9 | |
| Select one from each area: | ||
| Business Communication | ||
| COMMUNICATION STRATEGIES FOR MATH AND SCIENCE PROFESSIONALS | ||
| Project Management | ||
| PROJECT MANAGEMENT FOR MATH AND SCIENCE PROFESSIONALS | ||
| Other Topics | ||
| INTRODUCTION TO DATA SCIENCE AND ANALYTICS | ||
| DATA ORIENTED COMPUTING AND ANALYTICS | ||
| DATA STRATEGY AND GOVERNANCE | ||
| GEOSPATIAL PROGRAMMING | ||
| OPERATIONS MANAGEMENT (ADVANCED SYSTEMS ANALYSIS) | ||
| LEADERSHIP IN ORGANIZATIONS | ||
| MANAGEMENT PRACTICES AND TECHNIQUES | ||
| Internship (3 credit hours) | 3 | |
| INTERNSHIP IN APPLIED AND COMPUTATIONAL MATHEMATICS | ||
| Total Credit Hours | 30 | |