Submissions are evaluated using **Mean Squared Error (MSE)**. For interpretability, leaderboard scores are reported as **Root Mean Squared Error (RMSE)**:

$$
RMSE = \sqrt{\frac{1}{N} \sum_{i=1}^{N} (y_i - \hat{y}_i)^2}
$$

where \(y_i\) is the true course rating and \(\hat{y}_i\) is your predicted rating.

## Submission File
Your submission file should be a CSV with the following format:

id,course_rating
1001,4.5
1002,3.8
1003,4.2
## Tips
- Use metadata creatively: difficulty, topic, instructor reputation, and engagement metrics can all be predictive.
- Text features from titles and descriptions can significantly improve your model.
- Preprocessing, feature engineering, and ensemble models are encouraged.