Class 9 AI Important Questions, MCQs & Sample Paper
Revision is an important part of exam preparation. Practicing important questions helps students understand concepts, improve confidence, and identify topics that need more attention.
This article contains:
- Important short answer questions
- Long answer questions
- MCQs with answers
- Case-based questions
- Sample question paper
- Quick revision tips
These questions are prepared according to the CBSE Class 9 Artificial Intelligence (Code 417) syllabus.
Section A: Important Short Answer Questions
1. What is Artificial Intelligence?
Artificial Intelligence is a branch of computer science that enables machines to perform tasks that normally require human intelligence, such as learning, problem-solving, and decision-making.
2. Name the major domains of AI.
The major AI domains are:
- Data
- Computer Vision
- Natural Language Processing (NLP)
3. What is the purpose of AI?
AI helps machines analyze information, identify patterns, solve problems, and support human decision-making.
4. What is the AI Project Cycle?
The AI Project Cycle is a step-by-step process used to create AI solutions.
Its stages are:
- Problem Scoping
- Data Acquisition
- Data Exploration
- Modelling
- Evaluation
5. Explain Problem Scoping.
Problem Scoping is the first stage of the AI Project Cycle where the problem is identified, understood, and clearly defined.
6. What is Data Acquisition?
Data Acquisition is the process of collecting relevant data required for developing an AI solution.
7. Why is data important for AI?
AI systems learn from data. Good quality data helps AI models produce better results.
8. What is Computer Vision?
Computer Vision is an AI domain that allows computers to understand and analyze images and videos.
9. What is Natural Language Processing?
Natural Language Processing enables computers to understand and process human languages.
10. Define AI Ethics.
AI Ethics refers to principles that ensure AI systems are developed and used responsibly.
11. What is AI bias?
AI bias occurs when an AI system produces unfair results because of biased data or design.
12. What is Data Visualization?
Data Visualization is the graphical representation of information using charts, graphs, and tables.
13. Define Mean.
Mean is the average value of a set of numbers.
Formula:
Mean = Sum of values ÷ Number of values
14. Define Median.
Median is the middle value of data arranged in order.
15. Define Mode.
Mode is the value that appears most frequently in a data set.
16. What is Generative AI?
Generative AI is a type of AI that creates new content such as text, images, audio, and code.
17. What is a prompt?
A prompt is an instruction given to an AI system to generate a response.
18. What is Python?
Python is a high-level programming language used in AI, data science, and software development.
19. What is a variable?
A variable is a name used to store data values in a program.
20. Name four Python data types.
- Integer
- Float
- String
- Boolean
Section B: Important Long Answer Questions
Q1. Explain the AI Project Cycle.
Answer:
The AI Project Cycle is a structured method used for developing AI solutions.
The five stages are:
1. Problem Scoping
Understanding and defining the problem.
2. Data Acquisition
Collecting required information.
3. Data Exploration
Analyzing and preparing collected data.
4. Modelling
Creating and training an AI model.
5. Evaluation
Checking the performance of the AI model.
Q2. Explain the applications of Artificial Intelligence.
Answer:
AI is used in many areas:
Healthcare
AI helps analyze medical information and support diagnosis.
Education
AI provides personalized learning support.
Transportation
AI helps in navigation and traffic management.
Banking
AI detects fraud and improves customer services.
Agriculture
AI helps monitor crops and predict conditions.
Q3. Explain AI Ethics principles.
Answer:
Important AI Ethics principles include:
Fairness:
AI should provide equal treatment.
Privacy:
Personal information should be protected.
Transparency:
AI decisions should be understandable.
Accountability:
Humans should remain responsible for AI actions.
Safety:
AI systems should be secure and reliable.
Q4. Explain Generative AI with examples.
Answer:
Generative AI creates new content by learning patterns from existing data.
Examples:
- Text generation
- Image creation
- Code generation
- Music generation
It should be used responsibly because AI-generated information may sometimes contain errors.
Q5. Explain Python decision-making statements.
Answer:
Decision-making statements allow programs to choose actions based on conditions.
Examples:
if statement
Runs code when a condition is true.
if-else statement
Provides two possible choices based on a condition.
Section C: Multiple Choice Questions (MCQs)
1. AI stands for:
A. Automated Intelligence
B. Artificial Intelligence
C. Advanced Information
D. Artificial Internet
Answer: B
2. Which AI domain works with images?
A. NLP
B. Computer Vision
C. Data Entry
D. Statistics
Answer: B
3. The first stage of AI Project Cycle is:
A. Evaluation
B. Modelling
C. Problem Scoping
D. Testing
Answer: C
4. AI systems learn from:
A. Data
B. Keyboard
C. Printer
D. Monitor
Answer: A
5. Which principle protects personal information?
A. Bias
B. Privacy
C. Modelling
D. Automation
Answer: B
6. The average of numbers is called:
A. Mode
B. Median
C. Mean
D. Range
Answer: C
7. Python is a:
A. Hardware device
B. Programming language
C. Operating system
D. Search engine
Answer: B
8. Which function displays output in Python?
A. show()
B. output()
C. print()
D. display()
Answer: C
9. AI that creates new content is:
A. Traditional AI
B. Generative AI
C. Manual AI
D. Basic AI
Answer: B
10. A value stored in Python is held by:
A. Variable
B. Keyboard
C. Monitor
D. Folder
Answer: A
Section D: Case-Based Questions
Case Study 1
A school wants to create an AI system that predicts the number of students who may need extra academic support.
Questions:
1. Which AI Project Cycle stage identifies this problem?
Answer: Problem Scoping
2. What type of data may be required?
Answer: Student performance data, attendance records, and learning information.
3. Why is evaluation needed?
Answer: To check whether the AI system provides accurate predictions.
Case Study 2
A company develops an AI recruitment system.
Questions:
1. Which AI ethics principle is important here?
Answer: Fairness
2. Why should data be checked before training AI?
Answer: To avoid biased results.
3. Why is transparency required?
Answer: Users should understand how decisions are made.
Sample Question Paper
Section A (1 Mark Each)
- Define Artificial Intelligence.
- Name AI domains.
- What is data?
- Define Generative AI.
- What is Python?
Section B (2 Marks Each)
- Explain AI Ethics.
- Write two applications of AI.
- Explain Data Visualization.
- Define Mean and Mode.
Section C (3 Marks Each)
- Explain AI Project Cycle stages.
- Explain applications of Computer Vision.
- Explain Generative AI advantages and limitations.
Section D (5 Marks Each)
- Explain AI Project Cycle with suitable example.
- Explain ethical challenges in Artificial Intelligence.
- Describe Python basics with examples.
Final Revision Checklist
Before examination, students should revise:
✓ AI meaning and applications
✓ AI domains
✓ AI Project Cycle stages
✓ AI Ethics principles
✓ Data Literacy concepts
✓ Mean, Median, Mode, Probability
✓ Generative AI concepts
✓ Python basics
✓ Important definitions
✓ Practical programs
Summary
Regular practice with important questions and MCQs helps students strengthen their understanding of Artificial Intelligence concepts. Class 9 AI preparation should focus on understanding concepts, practicing Python programs, and learning how AI is applied responsibly in real life.
End of Class 9 AI Notes Series
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