AWS Certified AI Practitioner (AIF-C01) — Question 303

A company is developing an ML model to predict heart disease risk. The model uses patient data, such as age, cholesterol, blood pressure, smoking status, and exercise habits. The dataset includes a target value that indicates whether a patient has heart disease.

Which ML technique will meet these requirements?

Answer options

• A. Unsupervised learning
• B. Supervised learning
• C. Reinforcement learning
• D. Semi-supervised learning

Correct answer: B

Explanation

Supervised learning is the correct technique because the dataset contains a known target label (heart disease status) alongside the input features, allowing the model to learn the mapping from inputs to outputs. Unsupervised learning is incorrect as it is used for unlabeled data to find hidden structures, while reinforcement learning relies on an agent interacting with an environment to maximize rewards. Semi-supervised learning is used when only a small portion of the data is labeled, which does not apply to this fully labeled dataset.