The Titanic disaster remains one of the most analyzed historical events due to its tragic loss of life and the notable patterns among survivors (and probably very popular and available dataset :D). Using association rules, this project aims to uncover hidden relationships between passenger attributes and survival outcomes leveraging Apriori algorithm to find meaningful associations in the Titanic dataset, revealing patterns in demographics, ticket class, family structure, and embarkation points.This project is conducted using the Titanic dataset from Kaggle (https://www.kaggle.com/c/titanic/data?select=train.csv), transformed into a transaction-based format for association rule mining.