Applied and Computational Mathematics
The Applied and Computational Mathematics (ACM) program provides graduate-level education in applied mathematics for people whose goal is to develop comprehension of principles of applied mathematics and skills in employing those principles in industrial or scientific settings. It has three central themes: general principles and theories of applied mathematics, the construction and analysis of mathematical models, and the development and efficient execution of computational mathematical algorithms. Effective use of advanced applied mathematical techniques has become increasingly important in industrial settings as the amount of sophisticated simulation software has mushroomed. People are needed who can help engineers, scientists and managers in the precise formulation of complex problems and in selecting the analytical methods and software appropriate for their solution. These people should understand the algorithms underlying mathematical software and be able to implement additional mathematical algorithms knowledgeably and efficiently in the framework of existing software. Finally, these people need to be able to interpret the results of computations to others. It is the goal of the program to provide people with these skills.
The key components of this evening program involve the integration of applied mathematics, mathematical modeling and numerical analysis. The ACM program provides not only coursework in various areas of applied mathematics, but also opportunities for independent or collaborative work. These approaches to learning contribute to a student’s outlook and depth of understanding. The program supports the development and enhancement of students’ skills useful in industrial and scientific careers, and in other careers having applied mathematics as its primary focus. It is geared toward three groups of 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, and recent graduates who desire a deeper understanding of applied mathematics as an aid in launching a career.
Admission and Prerequisites
Admission to the ACM program as a regular student requires a BA or a BS degree in mathematics, computer and information science, engineering, a physical science or a life science earned from a program at an accredited institution with an average of B or better. Individuals with other degrees or less than a B average may be considered for conditional admission status and may be required to submit evidence of potential for success in a graduate program. An entering student should have completed three courses in Calculus, including multivariate calculus, plus introductory courses in Linear Algebra and Differential Equations. Deficiencies in prerequisites may be made up after entrance to the Graduate Program. However, credits received in courses elected to make up the deficiencies do not count toward the degree.
Application instructions can be found at: umdearborn.edu/gradapplynow
Each applicant should submit the following:
- Official transcripts from all universities attended.
- A one-page statement of purpose describing the applicant’s career goals and personal objectives in pursuing the program.
- Three letters of recommendation. At least one letter must be from an academic source.
- Students whose native language is not English are also required to satisfy the English Language Requirements for Admission which can be found in the General Information section of this catalog.
For more information, visit the ACM website or call 313-583-6321.
Graduate credit may be transferred from other accredited degree-granting universities with graduate degree programs for up to a maximum of 6 credit hours, or their equivalent. For universities on the quarter system, 9 credit hours is the equivalent of 6 semester credit hours. Graduate credit may be transferred from other University of Michigan campuses (Flint or Ann Arbor) for up to half the credits required for the degree.
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 15 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.
Specific Course Requirements
|Select one course from each of the following areas. At most, nine credit hours of these courses may count toward the 30 credit hours.||9|
|Advanced Calculus I|
|Fourier and Boundary|
|Func of a Complex Var with App|
|Intro to Numerical Analysis|
or MATH 573
|Modeling Specialization Areas|
|Select at least four courses from the modeling specialization areas listed below. Not all four may be from the same area.||12|
Linear and Discrete Models:
|Linear Algebra w/Applications|
|Applied Regression Analysis|
|Introduction to Wavelets|
|Fin Diff Meth for Diff Equat|
|Fin Elemnt Meth for Diff Equat|
|Fourier and Boundary|
|Mathematical Statistics II|
|Data Analysis and Modeling|
|Reliability & Survival Analys|
|Applied Regression Analysis|
|Multivariate Stat Analysis|
|Time Series Analysis|
|Project or Independent Research||3|
|Independent Research Project|
|Six credit hours of cognate courses outside the Department of Mathematics and Statistics are required. The courses should be selected from an approved list.||6|
|Total Credit Hours||30|
|Computer and Information Science|
|CIS 505||Algorithm Analysis and Design||3|
|CIS 515||Computer Graphics||3|
|CIS 527||Computer Networks||3|
|CIS 537||Advanced Networking and Distributed Systems||3|
|CIS 544||Computer and Network Security||3|
|CIS 551||Advanced Computer Graphics||3|
|CIS 552||Information Visualization and Virtualization||3|
|CIS 568||Data Mining||3|
|CIS 574||Compiler Design||3|
|CIS 575||Software Engineering Mgmt||3|
|CIS 652||Advanced Information Visualization and Virtualization||3|
|ECON 5015||Introduction to Econometrics||3|
|Electrical and Computer Engineering|
|ECE 552||Fuzzy Systems||3|
|ECE 555||Stochastic Processes||3|
|ECE 560||Modern Control Theory||3|
|ECE 565||Digital Control Systems||3|
|ECE 567||Nonlinear Control Systems||3|
|ECE 585||Pattern Recognition||3|
|ECE 665||Optimal Control Systems||3|
|Industrial and Manufacturing Systems Engineering|
|IMSE 500||Models of Oper Research||3|
|IMSE 510||Probability & Statistical Mod||3|
|IMSE 511||Design and Analysis of Exp||3|
|IMSE 514||Multivariate Statistics||3|
|IMSE 520||Managerial Decision Analysis||3|
|IMSE 567||Reliability Analysis||3|
|DS 570||Management Science||3|
|OM 521||Operations Management||3|
|OM 660||Supply Chain Analytics||3|
|ME 510||Finite Element Methods||3|
|ME 518||Advanced Engineering Analysis||3|
|PHYS 503||Electricity & Magnetism||3|
|PHYS 553||Quantum Mechanics||3|