Offers and investigates efficient Monte Carlo simulation methods in order to realize a Bayesian approach to approximate learning of Bayesian networks from both complete and incomplete data. This publication discusses basic concepts about probabilities, graph theory and conditional independence; and Bayesian network learning from data.