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.

Overview

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

pdfDownload 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).

PRE-REQUISITE KNOWLEDGE

Multivariate Calculus 



CORE REQUIREMENTS


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



SCIENTIFIC COMPUTING COURSES


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



APPLIED COMPUTING COURSES


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



RESEARCH PROJECT


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 pdfHERE 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 docxHERE. 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

PRE-REQUISITE KNOWLEDGE


M 408D: Differential and Integral Calculus

M 408M: Multivariable Calculus

CORE COMPUTING COURSE


EE 312: Introduction to Programming

SSC 222/322: Introduction to Scientific Programming

Equivalent course with consent of faculty advisor

CORE MATH COURSE

SSC 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

NUMERICAL METHODS ELECTIVES


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

SSC 335: Introduction to Scientific/Technical Computing

STATISTICAL METHODS ELECTIVE

S
EE 351K: Probability and Random Processes

M 358K: Applied Statistics

M 378K: Introduction to Mathematical Statistics

BME 335: Engineering Probability and Statistics 
Another statistics course with consent of faculty advisor

OTHER COMPUTING TOPICS ELECTIVES


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

SSC 329D: Practical Linear Algebra
II
SSC 374C: Parallel Computing

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

SSC 374E: Visualization and Data Analysis

APPLIED COMPUTING COURSE


ASE 347: Introduction to Computational Fluid Dynamics

BIO 321G: Computational Biology

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*

ECO 363C: Computational Economics

EE 379K: Introduction to Data Mining

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

Contact

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