Predictive Student Dropout Risk Assessment Framework

Construct a machine learning pipeline in Python that uses historical student spreadsheet data to predict dropout risks with high accuracy. Implement feature engineering techniques with pandas, develop a scikit-learn predictive model, and create an Excel-based reporting system that highlights individual student risk factors. Include probabilistic scoring, confidence intervals, and recommended intervention strategies directly embedded in the spreadsheet.