Quasi-newton optimizationCovers gradient line search methods and optimization techniques with an emphasis on Wolfe conditions and positive definiteness.
Optimization MethodsCovers optimization methods without constraints, including gradient and line search in the quadratic case.
Optimization MethodsCovers unconstrained and constrained optimization, optimal control, neural networks, and global optimization methods.
Finite Element MethodCovers the Finite Element Method, discussing the derivation of the equation of motion and exploring mass and stiffness matrices.
Finite Element ModelingCovers the derivation of the equation of motion, interpolation, Newton's equation, and energy conservation in finite element modeling.
Turbulence: Numerical Flow SimulationExplores turbulence characteristics, simulation methods, and modeling challenges, providing guidelines for choosing and validating turbulence models.
Runge Kutta MethodCovers the Runge Kutta method and its application to optimal control and neural networks.
Introduction to Data ScienceIntroduces the basics of data science, covering decision trees, machine learning advancements, and deep reinforcement learning.
