Introduction to Sampling

A guided path from probability to Monte Carlo methods.

A structured learning path that connects probability, distributions, the central limit theorem, Monte Carlo integration, and practical sampling algorithms.

We have started moving selected technical material into a guided Learning library. The first path is Introduction to Sampling, a sequence of runnable lessons that starts with probability and distributions, then builds toward the central limit theorem, Monte Carlo integration, inverse-transform sampling, rejection sampling, and importance sampling.

Open the learning path

If you want to jump straight into the first lesson, start with Probability.