Introduction to Monte Carlo Methods

This is a fully developed graduate-level course on Monte Carlo methods open to the public. I simplify much of the work created leaders in the field like Christian Robert and George Casella into easy to digest lectures with examples. 

The target audience is anyone with a background in programming and statistics with a specific interest in Bayesian computation. 

In this course, students tackle problems of generating random samples from target distributions through transformation methods and Markov Chains, optimizing numerical and combinatorial problems (i.e. Traveling Salesman Problem) and Bayesian computation for data analysis.

In this course, students have the opportunity to develop Monte Carlo algorithms into code "by hand" without needing to use "black-box" 3rd party packages.