A synthetic dataset of 1000 students is generated by combining study hours, attendance, previous scores, and participation. Each factor contributes to the final exam score using weighted rules.

The model learns average scores for each combination and then estimates your likely score range, along with **personalized improvement suggestions** for better performance.