Practice Exam Questions

---

Question 1

A real estate company wants to predict the selling price of a house based on its size, location, and age.

Which machine learning technique should be used?

A. Classification
B. Clustering
C. Regression
D. Anomaly detection

Correct Answer: C

Explanation:
The output is a numeric value (price), which makes this a regression scenario.

---

Question 2

A business wants to estimate the number of hours it will take to complete a project based on historical project data.

Which type of machine learning is most appropriate?

A. Regression
B. Classification
C. Clustering
D. Association

Correct Answer: A

Explanation:
Estimating time in hours is predicting a numeric value, which is a regression task.

---

Question 3

Which scenario is best suited for regression?

A. Determining whether a transaction is fraudulent
B. Grouping customers based on purchasing behavior
C. Predicting monthly sales revenue
D. Assigning customers to loyalty tiers

Correct Answer: C

Explanation:
Monthly sales revenue is a continuous numeric value, making regression the correct choice.

---

Question 4

An AI model predicts tomorrow’s temperature based on historical weather data.

What type of machine learning problem is this?

A. Classification
B. Regression
C. Clustering
D. Anomaly detection

Correct Answer: B

Explanation:
Temperature is a numeric measurement, so this is a regression problem.

---

Question 5

A company wants to predict how many units of a product will be sold next month.

Which machine learning technique should be used?

A. Regression
B. Classification
C. Clustering
D. Natural language processing

Correct Answer: A

Explanation:
The output is a quantity (number of units), which is best handled by regression.

---

Question 6

Which statement best describes a regression model?

A. It assigns data points to categories
B. It predicts continuous numeric values
C. It groups unlabeled data
D. It identifies unusual data points

Correct Answer: B

Explanation:
Regression models are used to predict numeric values, such as prices or quantities.

---

Question 7

An organization uses historical data to estimate the fuel consumption of delivery vehicles.

What type of machine learning scenario is this?

A. Classification
B. Clustering
C. Regression
D. Recommendation

Correct Answer: C

Explanation:
Fuel consumption is a numeric measurement, making this a regression scenario.

---

Question 8

Which output value most strongly indicates a regression problem?

A. Approved / Rejected
B. High / Medium / Low
C. Fraud / Not Fraud
D. 245.7

Correct Answer: D

Explanation:
A precise numeric output (245.7) indicates a regression scenario.

---

Question 9

A model predicts delivery times in hours based on distance, traffic, and weather.

Which machine learning technique is being used?

A. Classification
B. Regression
C. Clustering
D. Anomaly detection

Correct Answer: B

Explanation:
Delivery time in hours is a continuous numeric value, so regression is appropriate.

---

Question 10

On the AI-900 exam, which keyword most often signals a regression scenario?

A. Classify
B. Group
C. Detect
D. Estimate

Correct Answer: D

Explanation:
Words like estimate, predict, or forecast typically indicate regression problems.

---

Exam-Day Tip

If a machine learning related question asks “how much,” “how many,” or “how long”, the answer is typically Regression related.

---

Go to the AI-900 Exam Prep Hub main page.