Optimization for data science - Mines ParisTech (2020)

1. Optimality conditions
2. Stochastic gradient methods
   
3. The Frank-Wolfe method
4. (Projected) Subgradient method
5. DC Programming in a nutshell
   

Nonlinear Programming - CMA (2020)

1. Optimality conditions 
2. Algorithms for unconstrained optimization
3. Algorithms for constrained optimization
4. Project: The Hanging Chain problem
   

A minicourse on Stochastic Programming - CMA (2019)

1. Definitions and Examples,
   
2. Sample Average Approximation (SAA),  
3. Two-Stage Stochastic Linear Programming (2SLP),
   
4. L-Shaped Method, Gap estimation, 
5. Multistage Stochastic Programming
6. Chance Constrained Problems (slides by prof. René Henrion)
7. Project: Power Generation Planning under Uncertainty

Problem's data: 2SLP  Deterministic Equivalent  2SLP (new data problem)

Basic Course on Stochastic Programming - IMPA (2016) 

Cálculo Numérico - UERJ

•  Zeros reais de uma função real: Lista de exercícios Matlab: Método da Bisseção, Método da Falsa Posição, Método de Newton Raphson
• Sistemas lineares: Lista de exercícios  Matlab EG
• Sistemas lineares - métodos iterativos: Lista de exercícios Matlab: Método de Jacobi, Método de Gauss-Seidel
• Interpolação polinomial: Lista de exercícios Matlab: Método de Lagrange
• Mínimos quadrados: Lista de exercícios