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Lecture
Computational Science and Engineering: Master Program Overview
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Related lectures (24)
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Optimization with Constraints: Theory and Applications
Covers the theory and applications of optimization with constraints, including key concepts and numerical methods.
Differentiable Functions and Lagrange Multipliers
Covers differentiable functions, extreme points, and the Lagrange multiplier method for optimization.
Energy System Optimization
Covers the optimization of energy systems, focusing on solving equations and numerical methods.
Scientific Computing in Neuroscience
Explores the history and tools of scientific computing in neuroscience, emphasizing the simulation of neurons and networks.
Continuum Mechanics: Conservation Laws and Kinematics
Introduces continuum mechanics, focusing on conservation laws and kinematics for continuous media.
Efficient Stochastic Numerical Methods
Explores efficient stochastic numerical methods for modeling and learning, covering topics like the Analytical Engine and kinase inhibitors.
Nonlinear Equation Resolution: Introduction to Bisection Method
Introduces the bisection method for resolving nonlinear equations using numerical techniques and Python programming.
Energy Conversion Methods
Covers energy system, numerical methods, Newton-Raphson, convergence, and efficient equation solving.
Numerical Methods: Differential Equations and Stability Analysis
Covers numerical methods for solving differential equations and their stability analysis, focusing on error calculation and practical applications in engineering and science.
Scientific Computing with Python
Covers the basics of scientific computing with Python, focusing on programming, algorithms, and numerical methods.
