Your question is Missing Data and Feature Preparation. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
You're preparing a tabular dataset for a supervised learning task and need a clean training pipeline before comparing models.
How would you handle missing values, normalize data, and prepare datasets for modeling?