Lectures related to Numerical Methods: Order of Accuracy

Covers implicit schemes in numerical analysis for solving partial differential equations.

Numerical Differentiation: Backward and Central Differences

Explores backward and central differences for numerical differentiation, analyzing their properties and error analysis.

Introduces the Euler Forward Method for ODEs, focusing on error analysis and stability.

Numerical Methods: Bisection and Multidimensional Arrays

Discusses the bisection method for solving nonlinear equations and its implementation using Python with NumPy and Matplotlib.

System of ODEs

Explores numerical methods for solving ODE systems, stability regions, and absolute stability importance.

Fixed Point Theorem: Convergence of Newton's Method

Covers the fixed point theorem and the convergence of Newton's method, emphasizing the importance of function choice and derivative behavior for successful iteration.