
Courses
Numerical Root Finding Methods in Python and MATLAB: Video Tutorial
Implement bisection, a bracketed secant update and Newton-Raphson in Python and MATLAB. Compare assumptions, stopping criteria and two worked equations.
Video courses that teach a subject from the ground up, with the theory and line by line implementations in MATLAB and Python.
Topics include numerical computations, numerical methods, linear programming, genetic algorithms, particle swarm optimization and principal component analysis. Every course is free to watch, and the code is available to download.

Courses
Implement bisection, a bracketed secant update and Newton-Raphson in Python and MATLAB. Compare assumptions, stopping criteria and two worked equations.

Metaheuristics
Build binary and real-coded genetic algorithms in MATLAB and Python, with seven videos on selection, crossover, mutation, bounds, and implementation.

Courses
Learn PCA in Python and MATLAB, from covariance and eigenvectors to projection, reconstruction, explained variance, and worked iris and digits examples.

Courses
A guided MATLAB course covering equations, matrices, interpolation, integration, polynomials, differential equations and optimization, with links to all seven chapters.

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Model linear, integer, quadratic and nonlinear optimization problems in MATLAB. Follow worked examples and check feasibility, solver termination and local solutions.

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Solve initial value, boundary value and delay differential equations in MATLAB. Follow oscillator examples and check tolerances, boundary conditions and history functions.

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Work with MATLAB coefficient vectors to evaluate, fit, multiply, divide, differentiate and integrate polynomials. Check roots and division remainders.

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Compute integrals and derivatives in MATLAB using functions or sampled data. Explore quadrature, trapezoidal integration, gradients, tolerances and sample spacing.

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Compare polynomial fitting, grid interpolation, Fourier interpolation, splines and scattered-data methods in MATLAB, with practical checks for noisy data and extrapolation.

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Learn eigenvalues, eigenvectors and SVD in MATLAB, including diagonalization, low rank image approximation and checks on the reconstructed matrices.

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Solve polynomial, nonlinear and linear equations in MATLAB with roots, fzero, fsolve and linsolve. Compare the worked examples and learn how to check residuals.

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Fit linear-in-parameter models in MATLAB, Python and JavaScript. Learn intercepts, feature matrices, pseudoinverses, rank conditions and practical checks on prediction error.

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Solve linear difference equations using characteristic roots, initial conditions and particular solutions. Follow Fibonacci and repeated-root examples and verify each formula.

Courses
Build an RK4 solver in Python and MATLAB, simulate a predator-prey model and compare step sizes to understand accuracy and the limits of a fixed-step method.

Courses
Build linear programming models in MATLAB with linprog. Follow a worked maximization and a transportation model, then check constraints, bounds and variable ordering.

Metaheuristics
Learn PSO in three videos, from the update equations to a MATLAB implementation with position bounds, velocity limits, and constriction coefficients.