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



Download 36.77 Kb.
Date31.07.2017
Size36.77 Kb.
#25156




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

Name UT EID Email


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











Notes:

Download 36.77 Kb.

Share with your friends:




The database is protected by copyright ©ininet.org 2022
send message

    Main page