Problem
Can a student’s final grade be predicted from behavioural and historical data: study time, previous results, failures, and absences?
Approach
- Explored and preprocessed a student performance dataset
- Selected relevant features and split train/test data
- Trained a linear regression model and evaluated accuracy
Result
A working predictive model demonstrating how interpretable regression can surface which factors most influence academic outcomes, a foundation for more complex modelling approaches.
Stack
- Python
- Scikit-learn
- Pandas
Features used
The model incorporated study time, previous academic results, number of past failures, and absences, giving a multidimensional view of factors that correlate with final performance.