Think of a smart dashboard for a school that turns all the numbers about students’ grades, attendance, and activities into easy-to-read charts, so teachers and administrators can quickly spot which students might be falling behind and help them earlier.
Educators struggle to manually sift through scattered student records to identify at-risk students early. This use case centralizes student data and displays it visually so patterns of declining performance or engagement are visible sooner, enabling earlier interventions.
Institution-specific historical student performance data and embeddedness in academic workflows (advising, counseling, intervention committees).
Classical-ML (Scikit/XGBoost)
Structured SQL
Medium (Integration logic)
Data integration from heterogeneous student information systems and maintaining data quality across semesters and departments.
Early Majority
Focus on education-specific student record structures and visualizations tailored to early detection of academic risk rather than generic business analytics dashboards.