I liked that the task felt like real work. I got a messy, imbalanced dataset and had to build a model, then explain it to a non-technical manager on a single slide. It showed me that accuracy alone can be misleading, because the model with the highest accuracy found no real bookers. The Getting Started notebook gave me a clear way in, and the brief was easy to follow.

I liked that the simulation provided practical experience in data analysis and machine learning using a real-world business scenario. I learned how to prepare data, build a Random Forest model, evaluate its performance, and identify important factors influencing customer bookings. It helped me understand how data science can support business decisions.

I liked how the simulation provided practical experience in data analysis and machine learning using a real-world business scenario. I learned how to prepare data, build a Random Forest model, evaluate its performance, and identify the key factors influencing customer booking behaviour. It helped me understand how data science can support business decisions and improve customer targeting.