Allow students to master the approximation techniques used in numerical solutions that arise in science and engineering problems. Teach student show numerical methods work, what types and sources of errors to expect and when an application might lead to difficulties, solution of systems of linear equations for direct and indirect methods, Optimization, numerical integration, numerical interpolation, least square error and regression
Bachelor Degree in Computer Engineering
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| content serial | Description |
|---|---|
| 1 | Introduction to Numerical Analysis and course description |
| 2 | Solution of equation: Bisection method and Secant method |
| 3 | Solution of equation: False Position method and Newton Raphson method |
| 4 | Solution of equation: Berge Vieta method |
| 5 | Error Analysis: Definition of error, Source of errors, Types of errors |
| 6 | Error Analysis: Rounding off, Instability, Ill conditioning |
| 7 | 7thweek exam |
| 8 | Error Analysis: Error Propagation, Process Graph |
| 9 | Solution of system of linear equations: (Direct Methods) Gauss Elimination, Gauss Jordan, and LU Decomposition |
| 10 | Solution of system of linear equations: (Indirect Methods) Jacobi, Gauss Seidel |
| 11 | Unconstrained and Constrained Optimization |
| 12 | 12thweek exam |
| 13 | Numerical Interpolation: Mid-point, Trapezoidal, Simpson |
| 14 | Numerical Interpolation: Linear and Quadratic |
| 15 | Least square error and regression |
| 16 | |
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