The department of Mathematics and Statistics at University of Michigan-Dearborn currently offers a Master of Science Degree in Applied and Computational Mathematics.

The key components of this evening program involve the integration of applied mathematics, mathematical modeling and numerical analysis. 

More about the program

Effective use of advanced mathematical techniques has become more important in industrial settings in recent years owing to the fact that the applications of industry are addressed by implementing algorithms on the computer rather than by hand. The demand has increased for people who understand what algorithms do and how to implement mathematical algorithms knowledgeably and efficiently. The efficiency of an algorithm and of its implementation are issues which are often of major interest within a company. In-depth knowledge concerning this issue on the part of an employee or job applicant can increase greatly that individual’s value and ability to contribute. More generally, the skill of making advanced mathematical methods accessible is of increasing value both for research and for industrial applications. Development of skills in these areas is the primary purpose of the Master’s Degree Program in Applied and Computational Mathematics.

  • Provide graduate-level education in applied mathematics in order to develop comprehension of principles of applied mathematics and skills in employing those principles in industrial or scientific settings.


    • General principles and theories of applied mathematics.
    • Construction and analysis of mathematical models.
    • Development and efficient execution of computational mathematical algorithms.
    • Opportunities for independent or collaborative work.
    • Individuals in established careers who want or require further training for their current positions.
    • Individuals in the workforce who wish to retrain for new career directions, in some cases preparing for a more mathematically-oriented assignment with their current employer.
    • Recent graduates who desire a deeper understanding of applied mathematics as an aid in launching a career.
  • 1.   30 semester hours of graduate course work with a cumulative grade point average of B or better. The 30 hours must be selected from lists of approved courses and be approved by the student's graduate advisor. At least fifteen of the hours must be Mathematics and Statistics courses. Up to six credit hours toward the degree may be granted by the Graduate Program Committee to a student through the transfer of credit for approved graduate-level courses. Such courses must have been completed within the past five years with a grade of B or better at an accredited institution and not have been applied in whole or in part toward another degree or certificate.  In addition to the specific degree requirements listed here, the general Master's degree requirements of the Horace H. Rackham School of Graduate Studies as specified in The University of Michigan Bulletin:  Graduate Student Handbook also apply.


    2.   One course from each of the following Core Areas A, B, and C.  At most nine hours from these Core Areas may count toward the 30 hours.  Equivalent courses taken elsewhere may be used to satisfy the requirement, but may not count toward the 30 hours (with the exception of the six hours specified in 1 above which may count toward the 30 hours).

    A.  Mathematical Analysis

         i.   MATH 551 Advanced Calculus I

         ii.  MATH 554  Fourier Series and Boundary Value Problems

         iii. MATH 555  Complex Variables

    B.  Numerical Methods

         i.  MATH 572  Introduction to Numerical Analysis

         ii.  MATH 573  Matrix Computation

    C.  Modeling

         i.  MATH 562  Mathematical Modeling


    3.   At least four courses from the Modeling Specialization Areas listed below.  Not all four may be from the same area. Equivalent courses taken elsewhere may be used to satisfy the requirement, but may not count toward the 30 hours (with the exception of  the six hours specified in 1 above which may count toward the 30 hours).

    A.  Linear and Discrete Models

         i.  MATH 515  Approximation of Functions

         ii.  MATH 523  Linear Algebra with Applications

         iii.  STAT 530  Applied Regression Analysis

         iv.  MATH 558  Introduction to Wavelets

         v.  MATH 584  Applied and Algorithmic Graph Theory

    B.  Differential Models

         i.   MATH 504  Dynamical Systems

         ii.  MATH 514  Finite Difference Methods for Differential Equations

         iii.  MATH 516  Finite Element Methods for Differential Equations

         iv.  MATH 554  Fourier Series and Boundary Value Problems

      C.  Statistical Models

         i.   MATH 520  Stochastic Processes

         ii.   MATH 525  Mathematical Statistics II

         iii.  STAT 530   Applied Regression Analysis

         iv.  STAT 535   Data Analysis and Modeling

         v.   STAT 545   Reliability and Survival Analysis

         vi.   STAT 560   Time Series

    4.    MATH 599, Independent Research Project, taken for three credits.

    5.    Six hours of cognates outside the Department of Mathematics and Statistics. The courses should be selected from an approved list (Appendix B).

  • The following courses count toward the degree. Many of these courses have prerequisites beyond those required for admission to the program. If a student has only the courses required for admission to the program, the following courses should be accessible: IMSE 500, ME 510, ME 518, DS 570, OM 521. If a student takes IMSE 500, then IMSE 505 should be accessible.  If a student has taken a course in probability and statistics equivalent to IMSE 317, then the courses ECE 552, ECE 555, ECE 585 should be accessible.

    1.     Computer and Information Science

                  CIS 505     Algorithm Design and Analysis

                  CIS 515     Computer Graphics

                  CIS 527     Computer Networks

                  CIS 537     Advanced Networking

                  CIS 544     Computer and Network Security

                  CIS 551     Advanced Computer Graphics

                  CIS 552     Information Visualization and Multimedia Gaming

                  CIS 568     Data Mining

                  CIS 574     Compiler Design

                  CIS 575     Software Engineering Management

                  CIS 652     Information Visualization and Computer Animation

    2.     Economics

                   ECON 515     Introduction to Econometrics

    3.     Electrical and Computer Engineering

                   ECE 552     Fuzzy Systems

                   ECE 555     Stochastic Processes

                   ECE 560     Modern Control Theory

                   ECE 565     Digital Control

                   ECE 567     Non-linear Control Systems

                   ECE 585     Pattern Recognition

                   ECE 665     Optimal Control

    4.     Industrial and Manufacturing Systems Engineering

                   IMSE 500     Models of Operations Research

                   IMSE 505     Optimization

                   IMSE 510     Probability and Statistical Models

                   IMSE 511     Design and Analysis of Experiments

                   IMSE 514     Multivariate Statistics

                   IMSE 520     Managerial Decision Analysis

                   IMSE 567     Reliability Analysis

    5.  Management

                   DS 570      Management Science

                   OM 521     Operations Management

                   OM 660     Analysis and Design of Supply Chains

    6.  Mechanical Engineering

                   ME 510     Finite Element Methods

                   ME 518     Advanced Engineering Analysis

    7.  Physics

                   PHYS 503     Electricity and Magnetism

                   PHYS 553     Quantum Mechanics

    8.  Other graduate courses outside the Department of Mathematics and Statistics approved by the graduate advisor.