Graduate Degree

Industrial Mathematics - Master of Science

Industrial Mathematics - Master of Science
Plan Code:
Program Level:
Award Type:
Master of Science
College of Natural Science

Excerpt from the official Academic Programs Catalog:

Listed below are the approved requirements for the program from the official Academic Programs Catalog.
Students must consult their advisors to learn which specific requirements apply to their degree programs.

College of Natural Science

Department of Mathematics

Graduate Study
Industrial Mathematics - Master of Science

The degree of Master of Science in Industrial Mathematics is designed to produce generalized problem solvers of great versatility, capable of moving within an organization from task to task. The graduate will have acquired not only the standard mathematical and statistical tools and computer science principles to strengthen data analytic skills, but also the basic ideas of engineering and business, and will have received training in project development and in modes of industrial communication. The program is designed for students planning careers in business, government or industry.


To be admitted to the Master of Science in Industrial Mathematics program, a person should have completed (1) the mathematics or applied mathematics courses normally required for the bachelor’s degree with a major in mathematics, statistics, economics, physics or engineering, (2) courses at the senior level in mathematical analysis, linear algebra and differential equations, and (3) have some familiarity with mathematical software programs such as Mathematica, Matlab, etc.

Students entering the program are expected to have a mathematical preparation at the level of Mathematics 421, 414 and 442. Students with deficiencies may be required to take additional course work.

Requirements for the Master of Science Degree in Industrial Mathematics

In addition to meeting the requirements of the University and the College of Natural Science, the student must complete a total of 30 credits for the degree under Plan B (without thesis). The student’s program of study must be approved by the student’s academic advisor, including:

1. The following requirements for the major (30 credits):
a. Both of the following courses:
MTH 843 Survey of Industrial Mathematics 3
MTH 844 Projects in Industrial Mathematics 3
b. A minimum of two of the following courses:
MTH 810 Error-Correcting Codes 3
MTH 841 Boundary Value Problems I 3
MTH 842 Boundary Value Problems II 3
MTH 847 Partial Differential Equations I 3
MTH 848 Ordinary Differential Equations 3
MTH 849 Partial Differential Equations 3
MTH 850 Numerical Analysis I 3
MTH 851 Numerical Analysis II 3
MTH 852 Numerical Methods for Ordinary Differential Equations 3
MTH 880 Combinatorics I 3
MTH 881 Graph Theory 3
c. A minimum of two of the following courses:
STT 801 Design of Experiments 3
STT 802 Statistical Computation 3
STT 843 Multivariate Analysis 3
STT 844 Time Series Analysis 3
STT 847 Analysis of Survival Data 3
STT 861 Theory of Probability and Statistics I 3
STT 862 Theory of Probability and Statistics II 3
STT 863 Statistics Methods I 3
STT 864 Statistics Methods II 3
STT 866 Spatial Data Analysis 3
STT 875 R Programming for Data Sciences 3
STT 886 Stochastic Processes and Applications 4
STT 888 Stochastic Models in Finance 3
d. At least two of the following courses:
CMSE 801 Introduction to Computational Modeling 3
CMSE 802 Methods in Computational Modeling 3
CMSE 820 Mathematical Foundations of Data Science 3
CMSE 821 Numerical Methods for Differential Equations 3
CMSE 822 Parallel Computing 3
CMSE 823 Numerical Linear Algebra 3
CSE 802 Pattern Recognition and Analysis 3
CSE 803 Computer Vision 3
CSE 830 Design and Theory of Algorithms 3
CSE 835 Algorithmic Graph Theory 3
CSE 836 Probabilistic Models and Algorithms in Computational Biology 3
CSE 841 Artificial Intelligence 3
CSE 847 Machine Learning 3
CSE 860 Foundations of Computing 3
CSE 872 Advanced Computer Graphics 3
CSE 880 Advanced Database Systems 3
CSE 881 Data Mining 3
CSE 885 Artificial Neural Networks 3
EC 811A Mathematical Applications in Economics 2
EC 811B The Structure of Economic Analysis 2
EC 812A Microeconomics I 3
EC 812B Microeconomics II 3
EC 813A Macroeconomics I 3
EC 813B Macroeconomics II and its Mathematical Foundations 4
EC 820A Econometrics IA 3
EC 820B Econometrics IB 3
EC 821A Cross Section and Panel Data Econometrics I 3
EC 821B Cross Section and Panel Data Econometrics II 3
EC 822A Time Series Econometrics I 3
EC 822B Time Series Econometrics II 3
ECE 848 Evolutionary Computation 3
ECE 863 Analysis of Stochastic Systems 3
ME 830 Fluid Mechanics I 3
ME 840 Computational Fluid Dynamics and Heat Transfer 3
ME 872 Finite Element Method 3
MKT 805 Marketing Management 2
MKT 806 Marketing Research for Decision Making 3
MKT 816 Marketing Analysis 3
MKT 819 Advanced Marketing Research 3
MKT 864 Data Mining in Marketing 3
SCM 800 Supply Chain Management 3
SCM 815 Emerging Topics in Supply Management 3
SCM 826 Manufacturing Design and Analysis 1.5
SCM 833 Decision Support Models 2
SCM 843 Sustainable Supply Chain Management 2
SCM 853 Operations Strategy 2
SCM 854 Integrated Logistics Systems 1.5
e. Completion of a Certificate Program in Project Management. This requires completion of PHM 857 Project Management, covering such topics as formal project management culture, principles, knowledge areas, and terminology. It will normally be undertaken during the first year of enrollment with the opportunity to use the credit-no credit grading system. Certification will also require participation in Industrial Mathematics-specific discussion sessions. After the completion of the certificate program is approved by the instructors, the Industrial Mathematics Program, and the Associate Dean of the College of Natural Science, the Office of the Registrar will enter on the student’s academic record the name of the certificate program and the date it was completed. This certification will appear on the student’s transcript upon completion of the requirements for the degree program.