Course Outcomes (COs):
Course |
Learning outcome (at course level) |
Learning and teaching strategies |
Assessment Strategies |
|
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Course Code |
Course Title |
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24DPHY613(A) |
Numerical Methods and Application of MATLAB (Theory) |
CO130: Identify the sources of error Perform error analysis to understand the impact of errors on numerical solutions and also Evaluate the condition and stability of numerical algorithms. CO131: Find numerical solutions of the systems of linear and Non-linear equations with accuracy and obtain numerical solutions of algebraic transcendental equations. CO132: Solve initial and boundary value problems in differential equations using numerical methods and apply various numerical methods in real-life problems. CO133:Evaluate the accuracy and suitability of different curve fitting, interpolation, and extrapolation techniques for different types of data sets and applications. CO134: Develop the knowledge of MATLAB extension and will be able to apply these techniques to problem-solving in basic research field. CO135: Contribute effectively in Course specific interaction. |
Approach in teaching: Interactive Lectures, Discussion, Tutorials, Power point presentation, Demonstration, problem solving in tutorials
Learning activities for the students: Self learning assignments, Effective questions, Seminar presentation, Solving numericals |
Class test, Semester end examinations, Quiz, Solving problems, Assignments, Presentations |
Source of Errors, Round off error, Arithmetic error, error analysis, Condition and stability, method of undetermined coefficients, use of interpolation formula, iterated interpolation, inverse interpolation, Hermite interpolation and Spline interpolation (linear method).
Least square line, Methods of curve fitting, Interpolation by Spline functions, Fourier series and trigonometric polynomials, Bezier curve.
Introduction to Quadrature, Composite trapezoidal and Simpson’s Rule, Recursive rules, Adaptive Quadrature, Gauss-Legendre Integration.