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This notebook presents an end-to-end analysis of the Titanic dataset using Python. It includes data loading, data quality assessment, missing value handling, exploratory data analysis (EDA), and visualization of passenger survival patterns by gender, age, and passenger class. A Random Forest classifier is trained to predict passenger survival, and feature importance is analyzed to identify the factors that most influenced survival outcomes. This project demonstrates a complete data science workflow from raw data to actionable insights.