Module #10 Conjugate Gradient Method Introduction to conjugate gradient method and its applications
Module #11 Numerical Solution of Linear Systems Direct and iterative methods for solving linear systems
Module #12 Numerical Solution of Nonlinear Systems Bisection method, Newtons method, and fixed-point iteration for nonlinear systems
Module #13 Interpolation and Approximation Introduction to interpolation and approximation, polynomial interpolation, and spline interpolation
Module #14 Numerical Differentiation and Integration Numerical differentiation, numerical integration, and Gaussian quadrature
Module #15 Optimization under Uncertainty Introduction to optimization under uncertainty, probability theory, and uncertainty propagation
Module #16 Stochastic Optimization Methods Introduction to stochastic optimization methods, simulated annealing, and genetic algorithms
Module #17 Metaheuristics Introduction to metaheuristics, ant colony optimization, and particle swarm optimization
Module #18 Case Studies in Optimization Real-world applications of optimization techniques in fields such as logistics, finance, and energy
Module #19 Numerical Implementation of Optimization Algorithms Implementation of optimization algorithms using Python, MATLAB, or other programming languages
Module #20 Optimization Software and Tools Overview of optimization software and tools, such as Gurobi, CPLEX, and Python libraries
Module #21 Advanced Topics in Optimization Advanced topics in optimization, such as semidefinite programming and sum of squares optimization
Module #22 Optimization in Machine Learning Optimization techniques used in machine learning, such as gradient descent and stochastic gradient descent
Module #23 Optimization in Data Science Optimization techniques used in data science, such as recommendation systems and clustering
Module #24 Optimization in Engineering Optimization techniques used in engineering, such as structural optimization and control systems
Module #25 Multiobjective Optimization Introduction to multiobjective optimization, Pareto optimality, and multiobjective evolutionary algorithms
Module #26 Robust Optimization Introduction to robust optimization, robust linear programming, and uncertainty sets
Module #27 Stochastic Dynamic Programming Introduction to stochastic dynamic programming, Markov decision processes, and approximate dynamic programming
Module #28 Risk-Averse Optimization Introduction to risk-averse optimization, risk measures, and robust risk-averse optimization
Module #29 Optimization in Finance Optimization techniques used in finance, such as portfolio optimization and risk management
Module #30 Course Wrap-Up & Conclusion Planning next steps in Optimization Techniques and Numerical Solutions career
