This dataset is designed for practicing classification tasks, specifically predicting whether a student will pass or fail a course based on various academic and demographic factors. It contains 40,000 records of students, with attributes including study habits, attendance rates, previous grades, and more. The dataset also introduces challenges such as missing values, incorrect data, and noise, making it ideal for practicing data cleaning, exploratory data analysis (EDA), and feature engineering.