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. 

UM-Dearborn MS in Applied & Computational Mathematics
I love how small the classrooms are, how well you connect to your professors and get to know other students in your program.
Samantha Yassine, MS in Applied and Computational Mathematics, '17​

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.

Goals and Themes

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.
Example Prospective Students
  • 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.
Degree Requirements

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 policies and requirements also apply.  Note: Students admitted through Summer 2019 to the  Applied and Computational Math graduate program fall under Rackham Graduate School Academic Policies.


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 523  Linear Algebra with Applications

     ii.   STAT 530   Applied Regression Analysis

     iii.  MATH 558  Introduction to Wavelets

     iv.  MATH 573  Matrix Computation

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 550   Multivariate Statistical Analysis

     vii. 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).

Degree Requirements: Cognate Courses

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.

Office of Graduate Studies

Administration Building
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