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AI and Machine Learning Interview Questions

Total questions: 30

Worksheet time: 15mins

Name
Class
Date
1.

What is the basic definition of Artificial Intelligence (AI)?

a)

A computer that can only do math

b)

Systems or machines that mimic human intelligence to perform tasks

c)

A robot that moves like a human

d)

A high-speed internet connection

2.

Who is known as the "Father of AI" who proposed the Turing Test?

a)

Alan Turing

b)

Elon Musk

c)

Steve Jobs

d)

Bill Gates

3.

Which type of AI is designed to perform a specific task, like playing chess or recognizing a face?

a)

Super AI

b)

General AI (Strong AI)

c)

Narrow AI (Weak AI)

d)

Human AI

4.

What is "Artificial General Intelligence" (AGI)?

a)

AI that cannot learn new things

b)

AI used only in calculators

c)

AI that can understand and learn any intellectual task that a human can

d)

AI that is better than humans at everything

5.

Machine Learning (ML) is a _______ of Artificial Intelligence.

a)

Competitor

b)

Subset

c)

Replacement

d)

Different name

6.

In which type of learning does the model learn from "labeled" data (input-output pairs)?

a)

Manual Learning

b)

Reinforcement Learning

c)

Supervised Learning

d)

Unsupervised Learning

7.

Which type of learning is used to find hidden patterns or groupings in "unlabeled" data?

a)

Supervised Learning

b)

Teaching Learning

c)

Unsupervised Learning

d)

Semi-supervised Learning

8.

Reinforcement Learning is based on which concept?

a)

Reading books

b)

Labeled tables

c)

Trial and error with "Rewards" and "Penalties"

d)

Deleting data

9.

What is the correct order of the Machine Learning procedure?

a)

Model Training -> Collect Data -> Evaluation

b)

Evaluation -> Collect Data -> Analyze

c)

Collect Data -> Evaluation -> Model Training

d)

Collect Data -> Analyze -> Model Training -> Evaluation

10.

What is the first step in the machine learning process?

a)

Selling the product

b)

Evaluating the model

c)

Defining the problem and collecting data

d)

Writing code

11.

Which of the following is an example of AI in daily life?

a)

Smart Speakers (Alexa/Siri)

b)

Face ID on smartphones

c)

All of the above

d)

Recommendation systems (Netflix/YouTube)

12.

In the "Information Age," what is considered the "Fuel" for AI?

a)

Data

b)

Electricity

c)

Plastic

d)

Gasoline

13.

Which field uses AI to detect fraudulent bank transactions?

a)

Healthcare

b)

Entertainment

c)

Finance

d)

Agriculture

14.

What is "Deep Learning"?

a)

A subset of ML based on Artificial Neural Networks

b)

Learning while sleeping

c)

Simple linear math

d)

A way to store data in the ocean

15.

Which AI application helps in "Self-driving cars"?

a)

Calculator

b)

Email Spam Filter

c)

Computer Vision

d)

Digital Clock

16.

Which of these is a limitation of Machine Learning?

a)

It is often a "Black Box" (hard to explain how it decided)

b)

It can be biased if the data is biased

c)

All of the above

d)

It needs a lot of high-quality data

17.

What does "Bias" in AI mean?

a)

The AI is too fast

b)

The AI uses too much power

c)

Prejudiced or unfair results due to faulty data

d)

The AI is too expensive

18.

Which discipline is NOT typically related to AI/ML?

a)

Ancient History

b)

Statistics

c)

Mathematics

d)

Computer Science

19.

What is "Natural Language Processing" (NLP)?

a)

Teaching computers to understand human speech and text

b)

Teaching computers to grow trees

c)

Making computers run without electricity

d)

A type of physical exercise

20.

Why do we need Machine Learning instead of traditional programming?

a)

Because humans are lazy

b)

To solve problems where rules are too complex for humans to write manually

c)

To make computers heavier

d)

To reduce the number of colors on a screen

21.

Which algorithm is used for "Clustering" in Unsupervised Learning?

a)

Email Filter

b)

K-Means

c)

Linear Regression

d)

Decision Trees

22.

Which technique is used to predict a continuous value, like the price of a house?

a)

Classification

b)

Regression

c)

Clustering

d)

Association

23.

What is "Classification" used for?

a)

Grouping similar customers

b)

Predicting house prices

c)

Finding the shortest path on a map

d)

Categorizing data (e.g., Is this email "Spam" or "Not Spam"?)

24.

In AI, what does "Neural Networks" mimic?

a)

The human brain's structure (neurons)

b)

A spider web

c)

The human digestive system

d)

A telephone network

25.

Which era are we currently in, according to AI history?

a)

The Stone Age

b)

The Industrial Age

c)

The AI/Information Age

d)

The Steam Age

26.

What is the main objective of "Model Evaluation"?

a)

To change the color of the data

b)

To delete the model

c)

To check how accurately the model performs on new data

d)

To make the model look pretty

27.

Which of these is a "Supervised" task?

a)

Cleaning a hard drive

b)

Recommending a movie

c)

Predicting if a patient has a disease based on past records

d)

Grouping news articles by topic

28.

What is "Overfitting" in Machine Learning?

a)

When you have too much RAM

b)

When a model is too small

c)

When a model learns the training data too well but fails on new data

d)

When the computer gets too hot

29.

Which of the following is a "Big Data" characteristic that helps AI?

a)

Small size

b)

Variety and Volume

c)

Low speed

d)

Expensive cost

30.

AI that can outperform humans in every single field is called:

a)

Narrow AI

b)

Basic AI

c)

Weak AI

d)

Super AI