The Certificate in Scientific Computation is available to all undergraduates interested in the use of mathematical, statistical and computer-based techniques to investigate complex systems. Students must complete 18 semester hours of courses including an independent research project.


Students must complete 18 semester hours of courses as follows in "Course Requirements."

Scientific computation is the use of mathematical, statistical and computer-based techniques to investigate complex systems. In a world where computation is fueling innovation and success, a certificate in scientific computation will make you more competitive for jobs and top-tier graduate schools in your field.

Scientific computation has applications in science, engineering, economics, medicine, sociology and many other disciplines. For example, scientific computation has helped us to understand the causes and effects of climate change, financial catastrophes, and the motions of stars, to optimize the performance of mechanical systems, to model the human brain, to control the spread of disease, and to develop more effective medicines.

How to Apply

Download Application HERE

Please return all applications to GDC 7.408, Campus Mail Code: G2500.

Course Requirements

Track your progress with the pdfCourse Progression Worksheet.

(Click on bolded topics to go to a list of currently approved courses).


Multivariate Calculus 


Take one course in computer programming and one course in either Linear Algebra, Discrete Mathematics, or Differential Equations. 


Choose two of the following categories and take one course in each: Numerical Methods, Statistical Methods, Other Computing Topics. 


Select one computing course in an applied area of your choosing. 


Conduct independent research advised by a member of the SDS Scientific Computing faculty. Download register research course form to register for the independent study course. A final research report must be submitted upon completion of the course. Click HERE for more details on the report.

Frequently Asked Questions

Q: What are the requirements?

A: You will complete 18 semester hours, including a research project, as specified in the coursework guidelines. You must earn a letter grade of C- or better in all courses required for certification.

Q: How do I sign up?

A: Submit an application form to the SDS office in GDC 7.408, G2500. The form is available for download HERE. Students are encouraged to apply early in their course of study. The SDS department will help each student choose an appropriate course sequence and develop his or her independent study project.

Q: Can Certificate courses also fulfill my degree requirements?
A: Some courses that are required by the certificate will also fulfill degree requirements established by a student's major department. 

Q: Will the certificate appear on my transcript?

A: For students graduating in December 2010 or later, your official UT transcript will state that you completed the Undergraduate Certificate Program in Scientific Computation.

Approved Courses


M 408D: Differential and Integral Calculus

M 408M: Multivariable Calculus


ASE 201: Introduction to Computer Programming
BME 303: Introduction to Computing
CS 313E: Elements of Software Design
EE 312: Introduction to Programming
GEO 325J: Programming in FORTRAN and MATLAB

SDS 222/322: Introduction to Scientific Programming

Equivalent course with consent of faculty advisor


SDS 329C: Practical Linear Algebra I

M 340L: Matrices and Matrix Calculations

M 341: Linear Algebra and Matrix Theory
M 362M: Introduction to Stochastic Processes
M 427K:  Advanced Calculus for Applications


ASE 311: Engineering Computation

CE 379K: Computer Methods for Civil Engineering

CHE 348: Numerical Methods in Chemical Engineering

CS 323E: Elements of Scientific Computing

CS 323H: Scientific Computing–Honors

CS 367: Numerical Methods

M 348: Scientific Computation in Numerical Analysis

SDS 335: Introduction to Scientific/Technical Computing


BME 335: Engineering Probability and Statistics
ECO 329: Economic Statistics
EE 351K: Probability and Random Processes

M 358K: Applied Statistics

M 378K: Introduction to Mathematical Statistics

ME 335: Engineering Statistics
SDS 325H: Honors Statistics
SDS 328M: Biostatistics

Another statistics course with consent of faculty advisor


CS 324E: Elements of Graphics and Visualization

CS 327E: Elements of Databases

CS 329E: Topics in Elements of Computing*

CS 377: Principles and Applications of Parallel Programming

M 346: Applied Linear Algebra

M 362M: Introduction to Stochastic Processes

M 368K: Numerical Methods for Applications

M 372K: PDE and Applications

M 376C: Methods of Applied Mathematics

ME 367S: Simulation Modeling

MIS 325: Database Management
NEU 366M: Quantitative Methods
SDS 329D: Practical Linear Algebra II
SDS 374C: Parallel Computing

SDS 374D: Distributed and Grid Computing for Scientists and Engineers

SDS 374E: Visualization and Data Analysis


ASE 347: Introduction to Computational Fluid Dynamics

BIO 321G: Computational Biology

BIO 337J: Computational Biology Lab
BME 341: Engineering Tools for Computational Genomics Lab 

BME 342: Computational Biomechanics

BME 346: Computational Structural Biology

BME 377T: Topics in Biomedical Engineering

CH 368: Advanced Topics in Chemistry*

CS 329E: Topics in Elements of Computing*
CS 378: Introduction to Data Mining

ECO 363C: Computational Economics

EE 361/379K: Introduction to Data Mining

FIN 372/STA 372.6: Optimization Methods in Finance
GEO 325K: Computational Methods in Geological Sciences

M 375T: Topics in Mathematics*

M 474M: Mathematical Modeling in Science and Engineering

PHY 329: Introduction to Computational Physics

*Topics courses subject to approval based on course specific topics


For additional information about the Certificate in Scientific Computation program and application process, email Vicki Keller.