In collaboration with the Department of Mathematics, the Institute for Scientific Computation at Texas A&M University offers the Computational Technology and Science Certificate Program (CERT-CMTS), designed to meet the growing demand for advanced computational skills in science, engineering, and technology.
This multidisciplinary graduate certificate enhances students’ academic and professional development by equipping them with essential computational methodologies that complement their primary field of study. The program is especially well-suited for distance education students, with many elective courses available fully online.
To earn the certificate, students complete one core course, three electives, and a capstone project within their home department. Upon completion, students receive formal transcript recognition, boosting the value and marketability of their graduate degree and positioning them for leadership roles in academia and industry.
Enrollment Eligibility
To enroll in CERT-CMTS, students must:
- Be enrolled in a degree-seeking graduate program at Texas A&M
- Have a minimum cumulative GPA of 3.0
- Have completed at least two approved courses with a grade of B or higher, one being a core course
Completion Requirements
To be awarded the certificate, students must complete:
- One core course (MATH 609 or STAT 604)
- Three approved electives, with at least one outside the student's home department
- A capstone project:
- The project topic must be proposed and approved by ISC after the student has been formally admitted to the certificate program
- Projects completed, or coursework used as a project, before admission will not be accepted
Program Requirements
Students may begin taking qualifying coursework now and apply the credit retroactively once formally enrolled in the program. Coursework taken earlier will still count if it meets certificate standards. Capstone projects must be approved after admission.
| Core Courses. | Select one of the following. | 3 |
|---|---|---|
| STAT 604 | Topics in Statistical Computations | 3 |
| MATH 609 | Numerical Analysis | 4 |
| Elective Courses | Select three of the following, one of which must be exclusive of the student's home department1 | 9 |
|---|---|---|
| CSCE 608 | Database Systems | 3 |
| CSCE 626 | Parallel Algorithm Design and Analysis | 3 |
| CSCE 629 | Analysis of Algorithms | 3 |
| CSCE 640 | Quantum Algorithms | 3 |
| CSCE 649/VIZA 659 | Physically-Based Modeling | 3 |
| CSCE 659 | Parallel/Distributed Numerical Algorithms and Applications | 3 |
| CSCE 660/MATH 660 | Computational Linear Algebra | 3 |
| CSCE 735 | Parallel Computing | 3 |
| GEOP 620 | Geophysical Inverse Theory | 3 |
| MATH 610 | Numerical Methods in Partial Differential Equations | 3 |
| MATH 648 | Computational Algebraic Geometry | 3 |
| MATH 649 | Principles of Deep Learning | 3 |
| MATH 661 | Mathematical Theory of Finite Element Methods | 3 |
| MATH 676 | Finite Element Methods in Scientific Computing | 3 |
| MATH 677 | Mathematical Foundations for Data Science | 3 |
| MEEN 672 | Introduction to Finite Element Method | 3 |
| NUEN 618 | Multiphysics Computations in Nuclear Science and Engineering | 3 |
| NUEN 647 | Uncertainty Quantification and Data Science for Engineering Applications | 3 |
| PETE 656 | Advanced Numerical Methods for Reservoir Simulation | 3 |
| STAT 608 | Regression Analysis | 3 |
| STAT 624 | Databases and Computational Tools Used in Big Data | 3 |
| STAT 626 | Methods in Time Series Analysis | 3 |
| STAT 639 | Data Mining and Analysis | 3 |
| STAT 654 | Statistical Computing with R and Python | 3 |
| Other | ||
| Capstone Project2 | ||
| Total Semester Credit Hours | 12 |
- With the approval by the director of the Institute for Scientific Computation (ISC), student may substitute a course outside those listed as elective options. In such situations, the student must justify the substitution to and seek approval from the ISC's director prior to enrolling in the course. The director will include their support for the substitution in a memorandum to the Office of Graduate Studies (OGS) after the student files their degree plan with OGS and copies of these documents with the ISC.
- The capstone project's goal is to provide students with experience in the computational sciences. The capstone project may be fulfilled by:
- an independent study graduate course within the student's home department, or
- an independent study graduate course outside the student's home department, or
- as part of a MS thesis or project required by the student's home department, or
- as part of a PhD dissertation.
- To fulfill this requirement, the ISC's associate director or director must approve the capstone project, certify its computational component, and document its completion.