AWS Certified Machine Learning – Specialty — Question 288

A university wants to develop a targeted recruitment strategy to increase new student enrollment. A data scientist gathers information about the academic performance history of students. The data scientist wants to use the data to build student profiles. The university will use the profiles to direct resources to recruit students who are likely to enroll in the university.

Which combination of steps should the data scientist take to predict whether a particular student applicant is likely to enroll in the university? (Choose two.)

Answer options

• A. Use Amazon SageMaker Ground Truth to sort the data into two groups named "enrolled" or "not enrolled."
• B. Use a forecasting algorithm to run predictions.
• C. Use a regression algorithm to run predictions.
• D. Use a classification algorithm to run predictions.
• E. Use the built-in Amazon SageMaker k-means algorithm to cluster the data into two groups named "enrolled" or "not enrolled."

Correct answer: A, D

Explanation

To predict a binary outcome such as whether a student will enroll or not, a supervised learning approach is required. First, the data scientist must label the historical dataset into the two target classes using Amazon SageMaker Ground Truth. Then, a classification algorithm must be trained on this labeled data to predict the discrete class of new applicants, as regression is for continuous values and k-means is an unsupervised clustering technique.