A marketing team has customer data including age, income, and purchase history, but no labels indicating customer segments. They want to group customers into distinct segments for targeted campaigns. Which ML problem type and task should they use?

Reinforcement learning, clustering

Unsupervised learning, clustering

Supervised learning, classification

Semi-supervised learning, regression

A company wants to detect fraudulent transactions. They have a dataset with 99% legitimate transactions and 1% fraudulent ones. They want to minimize the cost of missing fraud, which is high, while keeping false alarms manageable. Which approach is most appropriate?

Use anomaly detection to identify rare fraudulent patterns

Use regression to predict the amount of fraud

Use clustering to group transactions and label the largest cluster as fraud

Use standard classification without addressing class imbalance

Certified Artificial Intelligence Practitioner (CAIP)

Domain 1Objective 4

Objective 1.4 Analyze Machine Learning System Use Cases AIP-210 Practice Questions (Page 5)

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 21–25

21application · medium
A marketing team has customer data including age, income, and purchase history, but no labels indicating customer segments. They want to group customers into distinct segments for targeted campaigns. Which ML problem type and task should they use?
Select an answer first
22application · medium
A bank wants to flag unusual transactions that could indicate fraud. They have a large dataset of normal transactions but very few confirmed fraud cases. They want to identify transactions that deviate from typical behavior. Which ML task is most appropriate?
Select an answer first
23foundation · easy
A logistics company wants to predict the exact delivery time in minutes for a package based on distance, traffic, and weather. Which machine learning task is most appropriate?
Select an answer first
24expert · hard
A company wants to detect fraudulent transactions. They have a dataset with 99% legitimate transactions and 1% fraudulent ones. They want to minimize the cost of missing fraud, which is high, while keeping false alarms manageable. Which approach is most appropriate?
Select an answer first
25foundation · easy
A company is considering an ML solution to automate customer support responses. Which of the following best represents a potential business impact of this solution?
Select an answer first

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Objective 1.4 Analyze Machine Learning System Use Cases AIP-210 Practice Questions (Page 5)

Questions 21–25

A marketing team has customer data including age, income, and purchase history, but no labels indicating customer segments. They want to group customers into distinct segments for targeted campaigns. Which ML problem type and task should they use?

A bank wants to flag unusual transactions that could indicate fraud. They have a large dataset of normal transactions but very few confirmed fraud cases. They want to identify transactions that deviate from typical behavior. Which ML task is most appropriate?

A logistics company wants to predict the exact delivery time in minutes for a package based on distance, traffic, and weather. Which machine learning task is most appropriate?

A company wants to detect fraudulent transactions. They have a dataset with 99% legitimate transactions and 1% fraudulent ones. They want to minimize the cost of missing fraud, which is high, while keeping false alarms manageable. Which approach is most appropriate?

A company is considering an ML solution to automate customer support responses. Which of the following best represents a potential business impact of this solution?

Keep studying — 1.0 Understanding the Artificial Intelligence Problem