I liked that the simulation provided practical experience with data science concepts and real-world business problems. The tasks helped me understand how data scientists approach problems such as customer churn, exploratory data analysis, feature engineering, and machine learning. It was a useful way to develop practical skills and gain a better understanding of data science work.

I really enjoyed the hands-on experience of working through a realistic data science project from start to finish. It helped me understand how data cleaning, exploratory analysis, feature engineering, modelling, and presenting business insights fit together. The tasks were practical and gave me a better understanding of how data science is applied to solve real business problems.

I liked that the simulation provided an end-to-end data science experience, from understanding the business problem and exploratory data analysis through feature engineering, predictive modeling, evaluation, and communicating insights to stakeholders. It was particularly useful to see how technical analysis can be connected to real business decisions and recommendations.