<s>[INST] I have a dataset of customer churn in a telecom company. The dataset contains 20,000 customers with the following variables:

- Churn (0 for no churn and 1 for churn)
- Age
- Income
- Customer Status (1 for residential and 2 for business)
- Phone Usage (1 for high, 2 for medium, and 3 for low)
- Account Length (in months)
- International Plan (1 for yes and 0 for no)
- Voice Mail Plan (1 for yes and 0 for no)
- Monthly Charge
- Total Charges

I want to predict the likelihood of customer churn based on the provided variables. 

What are your suggestions for data preparation, feature engineering, and modeling?[/INST]