NOC:MATLAB Programming for Numerical Computation


Lecture 1 - Course Introduction


Lecture 2 - Basics of Programming using MATLAB


Lecture 3 - Array Operations in MATLAB


Lecture 4 - Loops and Execution Control


Lecture 5 - Tutorial: Using Arrays


Lecture 6 - MATLAB Files -- Scripts and Functions


Lecture 7 - Plotting and Output


Lecture 8 - How to submit MATLAB Assignment


Lecture 9 - Errors in Numerical Computation


Lecture 10 - Truncation Errors and Taylors Series


Lecture 11 - Round-Off Errors; and Iterative Methods


Lecture 12 - Step-wise Methods and Error Propagation


Lecture 13 - How to get MATLAB Online access (for all enrolled students of this course)


Lecture 14 - Differentiation in Single Variable


Lecture 15 - Higher Order Differentiation Formulae


Lecture 16 - Partial Differentials (Bonus)


Lecture 17 - Numerical Integration


Lecture 18 - Multiple Applications of Integration Formulae


Lecture 19 - In-Build MATLAB Integration Functions


Lecture 20 - Basics of Linear Algebra


Lecture 21 - Gauss Elimination and Back-Substitution


Lecture 22 - LU Decomposition and Partial Pivoting


Lecture 23 - Gauss Siedel Method


Lecture 24 - (Tutorial)


Lecture 25 - Tri-Diagonal Matrix Algorithm


Lecture 26 - Nonlinear Equations in Single Variable


Lecture 27 - Using MATLAB command fzero


Lecture 28 - Fixed Point Iteration in Single Variable


Lecture 29 - Newton-Raphson (single variable)


Lecture 30 - Using MATLAB command fsolve (multi-variable)


Lecture 31 - Newton-Raphson (multi Variable)


Lecture 32 - Introduction


Lecture 33 - Linear Least Squares Regression


Lecture 34 - Nonlinear and Functional Regression


Lecture 35 - Interpolation Functions in MATLAB


Lecture 36 - Introduction and Euler\'s Method


Lecture 37 - Runge-Kutta (RK-2) method


Lecture 38 - MATLAB ode45 algorithm


Lecture 39 - Higher order Runge-Kutta Methods


Lecture 40 - Error Analysis


Lecture 41 - Multi-Variable ODE


Lecture 42 - Stiff Systems & Solution using ode15s


Lecture 43 - Method of Lines for transient PDEs


Lecture 44 - A Final Example


Lecture 45 - Tutorial: How to do linear and nonlinear regression