AI and ML Fundamentals CLOUD-DIGITAL-LEADER Practice Questions (Page 2)

Questions 6–10

1. 6foundation · easy

   A company trains a customer churn prediction model using historical data that contains many duplicate and outdated records. What is the most likely impact?

   • AThe model will be slower to train but still accurate.
   • BThe model may learn incorrect patterns, leading to poor predictions.
   • CThe model will automatically filter out bad data during training.
   • DThe model will be more accurate because it has more data.
   Reveal Solution Discussion Select an answer first
2. 7expert · hard

   A logistics company wants to optimize delivery routes. They have historical data on delivery times, traffic patterns, and package weights. They want to predict the optimal route for each delivery to minimize time and fuel consumption. Which type of ML problem is this?

   • AClustering, because they are grouping similar deliveries.
   • BClassification, because they are choosing among a set of possible routes.
   • CA combination of regression and optimization techniques.
   • DRegression, because they are predicting a continuous value (delivery time).
   Reveal Solution Discussion Select an answer first
4. 8foundation · easy

   Why is high-quality data essential for machine learning models?

   • ABecause models learn patterns from data, so poor-quality data leads to inaccurate or biased predictions.
   • BBecause data quality only matters for large datasets, not small ones.
   • CBecause models can automatically correct errors in the data during training.
   • DBecause high-quality data guarantees the model will be 100% accurate.
   Reveal Solution Discussion Select an answer first
5. 9foundation · easy

   Why is explainable AI important for building trust in machine learning models?

   • AIt allows stakeholders to understand how a model makes decisions, which helps identify biases and errors.
   • BIt guarantees that the model will be 100% accurate.
   • CIt makes the model faster and more efficient.
   • DIt allows the model to be used without any human oversight.
   Reveal Solution Discussion Select an answer first
6. 10foundation · easy

   A bank wants to build a model that predicts whether a loan applicant will default (yes or no). Which type of machine learning problem is this?

   • AClustering
   • BClassification
   • CRegression
   • DReinforcement learning
   Reveal Solution Discussion Select an answer first