This course covers practical implementation of optimization, knapsack (bin packing) problems, decision trees and dynamic programming. It includes some graph problems, plotting, stochastic thinking and coding random walks. It is based in inferential statistics, using Monte Carlo simulations, k-fold clustering and regression to the mean. The link below takes you to my GitHub repo covering the course.
Python, pylab (random, time, plot, polyfit).