Ut certificate in Scientific Computation—Progression Worksheet Last updated 10/26/2016

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UT Certificate in Scientific Computation—Progression Worksheet Last updated 10/26/2016

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Use this worksheet to plan and document your coursework as you proceed through the certificate program and please bring it to all meetings with your certificate program advisor(s).

II. Core Requirements

Semester Taken

A. Computer Programming (choose one)

ASE 301

BME 303 CS 313E EE 312 GEO 325J SDS 322

Introduction to Computer Programming Introduction to Computing

Elements of Software Design

Software Design and Implementation Programming in FORTRAN & MATLAB

Introduction to Scientific Programming (recommended)

B. Mathematics (choose one)

*Blue highlight = offered Spring 2017

I. Prerequisite Knowledge

(Choose one)

Semester Taken

M 408D Differential and Integral Calculus

M 408M Multivariable Calculus

SDS 329C

Practical Linear Algebra I

M 427J

Differential Equations with Linear Algebra

M 340L

Matrices and Matrix Calculations

M 341

Linear Algebra and Matrix Theory

M 362M

Introduction to Stochastic Processes

III. Scientific Computing Courses

Semester Taken

(Choose two categories and take one course in each.)

A. Numerical Methods

ASE 211K 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

M 368K Numerical Methods for Applications

SDS 335 Scientific & Technical Computing

B. Statistical Methods

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 Honor Statistics SDS 328M Biostatistics

Another statistics course with consent of faculty advisor

Course Name & Number: _
C. Other Computing Topics

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 & Grid Computing for Sci. & Engineers

SDS 374E

Visualization and Data Analysis

ASE 347

Introduction to Computational Fluid Dynamics

BIO 321G

Intro to Computational Bio

BIO 377J

Computational Biology 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 361M

Introduction to Data Mining

V. Research Project

SDS 2/3/479R Undergraduate Research

Semester Taken

IV. Applied Computing Courses (choose one)

Semester Taken

FIN 372/STA 372.6 Optimization Methods in Finance

GEO 325K Computational Methods in Geological Sciences M 375T

M 374M PHY 329

Topics in Mathematics*

Mathematical Modeling in Science and Engineering Introduction to Computational Physics


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