Key information #
| Instructor | Prashant K. Jha |
| prashant.jha@austin.utexas.edu, pjha.sci@gmail.com | |
| Title of course | Engineering Computation |
| Course unique number | 14610 |
| Office hours | Wednesday 6:00 - 7:30 pm, Thursday 6:00 - 7:30 pm |
| Lecture room | ASE 1.126, map: 2617 Wichita St, Austin, TX 78712 |
| Lecture time | MWF 9:00 am - 10:00 am |
| Canvas webpage | Section 1 (14610) |
| Github repository | COE-311K-Fall2021 |
Syllabus pdf #
Download from this link
Teaching assistants #
TA: Brad Marvin (brad_marvin@utexas.edu)
Office hours: TBA
Textbook #
We will use the following book as a main reference
Applied Numerical Methods with Matlab for Engineers & Scientists by Steven C. Chapra. 3rd Ed., McGraw-Hill, 2012
Note: 3rd and 4th editions are somewhat syllabus so you could also use 4th edition of the book, however, instructor and TA/LA will use 3rd edition is main reference.
Assignment, exams, and grading policy #
These are discussed here
Topics to be covered #
| Topic number | Topic | Chapters in reference | Number of lectures |
|---|---|---|---|
| 1 | Introduction to MATLAB | 2, 3 | 4 |
| 2 | Sources of Error in Computer Arithmetic and Algorithms | 4 | 1 |
| 3 | Roots and optimization | 5, 6, 7 | 4 |
| 4 | Linear system of equations | 8, 9, 12 | 6 |
| 5 | Eigenvalues and eigenvectors | 13 | 3 |
| 6 | Regression, curve fitting, least squares | 14, 15 | 3 |
| 7 | Polynomial Interpolation | 17 | 3 |
| 8 | Numerical integration | 19, 20 | 3 |
| 9 | Numerical differentiation | 21 | 3 |
| 10 | Numerical methods for differential equations | 22, 24 | 4 |
| 11 | Brief introduction to Artificial Neural Networks and their applications | 3 - 4 |
Lecture plans and important dates #
See the details in this syllabus pdf file: syllabus pdf.