Build an academic analytics system that evaluates student performance patterns to predict academic success and identify at-risk students. The platform will support data-driven decision-making in educational institutions.
Collect academic records and attendance data.
Perform data preprocessing.
Identify performance indicators.
Implement classification models.
Analyze trends and patterns.
Develop dashboards for faculty.
Generate predictive risk scores.
Test model reliability.
Ensure privacy compliance.
Prepare detailed reports.
