The identification of frequent item sets and of association rules have received a lot of attention in data mining due to their many applications in marketing, advertising, inventory control, and many other areas. First the notion of frequent item set is introduced and we study in detail the most popular algorithm for item set identification: the Apriori algorithm. Next we present the role of frequent item sets in the identification of association rules and examine the levelwise algorithms, an important generalization of the Apriori algorithm.