A startup wants to build an ML model to predict customer lifetime value. They have only 1,000 customer records, but they believe the model will significantly increase revenue. They have a small budget and need a working model in two months. What is the most realistic approach?

Start with a simple model using the available data, and plan to collect more data over time

Wait until they have 100,000 records before starting

Hire a large data science team to build a complex model

Use a deep learning model to maximize accuracy

A logistics company wants to predict the exact delivery time (in minutes) for each shipment based on distance, traffic, weather, and package weight. They have historical data with these features and the actual delivery times. Which ML problem type and task should they use?

Supervised learning, regression

Reinforcement learning, regression

Unsupervised learning, clustering

Supervised learning, classification

A hospital wants to deploy an ML model to predict patient readmission risk. Which of the following is a key stakeholder group that must be involved?

Clinical staff (doctors and nurses)

A startup wants to use ML to predict stock prices with high accuracy to make trading decisions. Which factor most likely makes this use case infeasible?

Problem complexity and unpredictability

Certified Artificial Intelligence Practitioner (CAIP)

Domain 1Objective 4

Objective 1.4 Analyze Machine Learning System Use Cases AIP-210 Practice Questions (Page 3)

Part of the 1.0 Understanding the Artificial Intelligence Problem domain, which accounts for 26% of the AIP-210 exam.

30questions here

6free pages

6concepts

26%of the exam

Questions 11–15

11expert · hard
A startup wants to build an ML model to predict customer lifetime value. They have only 1,000 customer records, but they believe the model will significantly increase revenue. They have a small budget and need a working model in two months. What is the most realistic approach?
Select an answer first
12foundation · easy
A retail company wants to use historical purchase data to recommend products to individual customers. Which machine learning use case does this represent?
Select an answer first
13application · medium
A logistics company wants to predict the exact delivery time (in minutes) for each shipment based on distance, traffic, weather, and package weight. They have historical data with these features and the actual delivery times. Which ML problem type and task should they use?
Select an answer first
14foundation · easy
A hospital wants to deploy an ML model to predict patient readmission risk. Which of the following is a key stakeholder group that must be involved?
Select an answer first
15foundation · easy
A startup wants to use ML to predict stock prices with high accuracy to make trading decisions. Which factor most likely makes this use case infeasible?
Select an answer first

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