I really liked how the program provided hands-on tasks that reflected real-world data science challenges at Lloyds Banking Group. It helped me understand how data-driven insights support business decisions and customer retention strategies. The structure and clarity made it easy to follow and learn at my own pace.

I really appreciated the practical, real-world focus of the program. It gave me the chance to apply data-driven thinking to a meaningful business problem like customer retention. The balance between technical tasks and business context helped me understand how predictive analytics directly supports strategic decision-making.

What I liked about the simulation was that it showed the full process of building a churn prediction model from start to finish. It clearly connected data preparation, model building, and evaluation to real business outcomes. It also helped demonstrate how different choices, like handling imbalanced data and selecting evaluation metrics, affect the final results and decisions.