The tasks felt very realistic — building a lounge eligibility lookup table and a predictive model for customer bookings gave me hands-on experience with real business problems. I liked that the second task let me apply actual machine learning (feature engineering, RandomForest, cross-validation) rather than just theory.

The task used real flight and booking data rather than a purely theoretical exercise, which made it feel close to how BA's Airport Planning and Data Science teams actually work — from building an eligibility model with limited data to training a classification model and presenting results to a non-technical stakeholder.

I liked the simulation because it was interactive and practical It allowed me to apply what I had learned, make decisions, and immediately see the results of those decisions. It also helped me understand the importance of analysing data, testing different approaches, and learning from mistakes in a realistic environment.