Artificial Intelligence Class 9

Teachers and Examiners collaborated to create the Neural Network Class 9 MCQ. All the important MCQs are taken from the NCERT Textbook Artificial Intelligence ( 417 ) class IX.

Neural Network Class 9 MCQ

1. Choose the option that is not a type of learning from the list below.
a. Supervised Learning
b. Unsupervised Learning
c. Reinforcement Learning
d. None of the above 

Neural Network Class 9 MCQ

2. Identify the type of “facial identities for facial expressions” learning algorithm.
a. General patterns
b. Unsupervised patterns
c. Recognition patterns 
d. None of the above

3. What is the term for applying machine learning techniques to a large database?
a. Data encapsulation
b. Database
c. Data mining 
d. None of the above

4. Determine the type of learning that uses labelled training data.
a. Supervised Learning 
b. Unsupervised Learning
c. Reinforcement Learning
d. All of the above

5. What is the word for the process through which machine learning algorithms construct a model from sample data?
a. Transfer data modeling
b. Data training
c. Training data 
d. All of the above

Neural Network Class 9 MCQ

6. Which of the following is a subset of machine learning?
a. Artificial Intelligence
b. Data Learning
c. Deep Learning
d. All of the above

7. What are the various types of learning algorithms?
a. Supervised Learning
b. Unsupervised Learning
c. Reinforcement Learning
d. All of the above 

8. A approach of building artificial intelligence that involves training a computer algorithm on input data that has been tagged for a specific output is known as ______________.
a. Supervised Learning 
b. Unsupervised Learning
c. Reinforcement Learning
d. All of the above

Neural Network Class 9 MCQ

9. The use of Artificial Intelligence (AI) systems to detect patterns in data sets that aren’t categorized or labelled is referred to as _______________.
a. Supervised Learning
b. Unsupervised Learning 
c. Reinforcement Learning
d. All of the above

10. An intelligent agent interacts with the environment and learns to operate within that environment through ____________
a. Supervised Learning
b. Unsupervised Learning
c. Reinforcement Learning 
d. All of the above

11. A __________ is an artificial intelligence strategy for teaching computers to analyze data in the same way that the human brain does.
a. Neural Network 
b. Cell Network
c. Brain Network
d. None of the above

12. What are the features of a Neural Network ______________.
a. The human brain and nervous system are used to model neural network systems.
b. They can automatically extract features without the programmer’s input.
c. Every node in a neural network is a machine learning algorithm.
d. All of the above 

Employability skills Class 9 Notes

• Unit 1 – Communication Skills Class 9 Notes
• Unit 2 – Self-Management Skills Class 9 Notes
• Unit 3 – Basic ICT Skills Class 9 Notes
• Unit 4 – Entrepreneurial Skills Class 9 Notes
• Unit 5 – Green Skills Class 9 Notes

Employability skills Class 9 MCQ

• Unit 1 – Communication Skills Class 9 MCQ
• Unit 2 – Self-Management Skills Class 9 MCQ
• Unit 3 – Basic ICT Skills Class 9 MCQ
• Unit 4 – Entrepreneurial Skillls Class 9 MCQ
• Unit 5 – Green Skills Class 9 MCQ

Employability skills Class 9 Questions and Answers

• Unit 1 – Communication Skills Class 9 Questionns and Answers
• Unit 2 – Self-Management Skills Class 9 Questions and Answers
• Unit 3 – Basic ICT Skills Class 9 Questions and Answers
• Unit 4 – Entrepreneurial Skills Class 9 Questions and Answers
• Unit 5 – Green Skills Class 9 Questions and Answers

Aritificial Intelligence Class 9 Notes

• Unit 1 – Introduction to Artificial Intelligence Class 9 Notes
• Unit 2 – AI Project Cycle Class 9 Notes
• Unit 3 – Neural Network Class 9 Notes
• Unit 4 – Introduction to Python Class 9 Notes
• Unit 4 : Introduction to Tools for AI Class 9 Notes
• Unit 4 : Flow of Control in Python Class 9 Notes
• Unit 4 : Introduction to Packages Python Class 9 Notes

Aritificial Intelligence Class 9 MCQ

• Unit 1 – Introduction to Artificial Intelligence Class 9 MCQ
• Unit 2 – AI Project Cycle Class 9 MCQ
• Unit 3 – Neural Network Class 9 MCQ
• Unit 4 – Introduction to Python Class 9 MCQ

Artificial Intelligence Class 9 Questions and Answers

• Unit 1 – Introduction to Artificial Intelligence Class 9 Questions and Answers
• Unit 2 – AI Project Cycle Class 9 Questions and Answers
• Unit 3 – Neural Network Class 9 Questions and Answers
• Unit 4 – Introduction to Python Class 9 Questions and Answers

Reference Textbook

The above Neural Network Class 9 MCQ was created using the NCERT Book and Study Material accessible on the CBSE ACADEMIC as a reference.

Disclaimer (CBSESkillEducation)- 100% of the questions are taken from the CBSE textbook Neural Network Class 9 MCQ, and our team has tried to collect all the correct MCQs from the textbook . If you found any suggestion or any error please contact us anuraganand2017@gmail.com.

Teachers and Examiners (CBSESkillEduction) collaborated to create the Neural Network Class 9 Notes. All the important Information are taken from the NCERT Textbook Artificial Intelligence (417).

Neural Network Class 9 Notes

Algorithm

An algorithm is a set of instructions used in machine learning that allows a computer programme to mimic how a human learns to classify certain types of data.

a. Supervised Learning 

Supervised learning is a method of developing artificial intelligence that involves training a computer algorithm on input data that has been labeled for a certain output.

Example of Supervised Learning
You obtain a set of photographs with descriptions of what’s on them, and then you train a model to detect fresh photos.

b. Unsupervised Learning

The use of artificial intelligence (AI) systems to find patterns in data sets including data points that are neither categorized nor labeled is known as unsupervised learning.

Example of Unsupervised Learning
Assume the unsupervised learning algorithm is given an input dataset with photographs of various cats and dogs. The algorithm is never trained on the given dataset, therefore it has no knowledge what the dataset’s characteristics are.

c. Reinforcement Learning

“An intelligent agent interacts with the environment and learns to operate within that environment through reinforcement learning.”

Example of Reinforcement Learning

Neural Network

Warren McCulloch and Walter Pitts proposed neural networks for the first time in 1944.

A neural network is an artificial intelligence strategy for teaching computers to analyze data in the same way that the human brain does. Deep learning is a form of machine learning technique that employs interconnected nodes or neurons in a layered structure to mimic the human brain. It develops an adaptive framework that allows computers to learn from their errors and continuously improve.

Some of the features of a Neural Network are listed below:

1. The human brain and nervous system are used to model neural network systems.
2. They can automatically extract features without the programmer’s input.
3. Every node in a neural network is a machine learning algorithm.
4. It comes in handy while working on difficulties with a large data set.

Neural Networks Vs Human Nervous System

In the subject of Neural Network research, the biological brain and Artificial Neural Networks are two of the most challenging areas of study.

a. SIZE: The human brain contains 86 billion neurons and over 100 trillion connections that transmit electrical information throughout the body. The number of neurons in the artificial neural network is far lower.

b. MEMORY: The primary distinction is that humans forget, whereas neural networks do not. A neural network that has been properly trained.

c. ENERGY CONSUMPTION: The biological brain uses roughly 20% of the total energy consumed by the human body. Artificial constructions can’t even come close to matching the efficiency level of a biological brain, which operates on roughly 20 watts.

Employability skills Class 9 Notes

• Unit 1 – Communication Skills Class 9 Notes
• Unit 2 – Self-Management Skills Class 9 Notes
• Unit 3 – Basic ICT Skills Class 9 Notes
• Unit 4 – Entrepreneurial Skills Class 9 Notes
• Unit 5 – Green Skills Class 9 Notes

Employability skills Class 9 MCQ

• Unit 1 – Communication Skills Class 9 MCQ
• Unit 2 – Self-Management Skills Class 9 MCQ
• Unit 3 – Basic ICT Skills Class 9 MCQ
• Unit 4 – Entrepreneurial Skillls Class 9 MCQ
• Unit 5 – Green Skills Class 9 MCQ

Employability skills Class 9 Questions and Answers

• Unit 1 – Communication Skills Class 9 Questionns and Answers
• Unit 2 – Self-Management Skills Class 9 Questions and Answers
• Unit 3 – Basic ICT Skills Class 9 Questions and Answers
• Unit 4 – Entrepreneurial Skills Class 9 Questions and Answers
• Unit 5 – Green Skills Class 9 Questions and Answers

Aritificial Intelligence Class 9 Notes

• Unit 1 – Introduction to Artificial Intelligence Class 9 Notes
• Unit 2 – AI Project Cycle Class 9 Notes
• Unit 3 – Neural Network Class 9 Notes
• Unit 4 – Introduction to Python Class 9 Notes
• Unit 4 : Introduction to Tools for AI Class 9 Notes
• Unit 4 : Flow of Control in Python Class 9 Notes
• Unit 4 : Introduction to Packages Python Class 9 Notes

Aritificial Intelligence Class 9 MCQ

• Unit 1 – Introduction to Artificial Intelligence Class 9 MCQ
• Unit 2 – AI Project Cycle Class 9 MCQ
• Unit 3 – Neural Network Class 9 MCQ
• Unit 4 – Introduction to Python Class 9 MCQ

Artificial Intelligence Class 9 Questions and Answers

• Unit 1 – Introduction to Artificial Intelligence Class 9 Questions and Answers
• Unit 2 – AI Project Cycle Class 9 Questions and Answers
• Unit 3 – Neural Network Class 9 Questions and Answers
• Unit 4 – Introduction to Python Class 9 Questions and Answers

Reference Textbook

The above Neural Network Class 9 Notes was created using the NCERT Book and Study Material accessible on the CBSE ACADEMIC as a reference.

Disclaimer – 100% of the questions are taken from the CBSE textbook Neural Network Class 9, our team has tried to collect all the correct Information from the textbook . If you found any suggestion or any error please contact us anuraganand2017@gmail.com.

Teachers and Examiners collaborated to create the AI Project Cycle Class 9 Questions and Answers. All the important QA are taken from the NCERT Textbook Artificial Intelligence ( 417 ) class IX.

AI Project Cycle Class 9 Questions and Answers

1. What is the AI Project Cycle?

Answer – The AI Project Cycle is a step-by-step process that a company must follow in order to derive value from an AI project and to solve the problem.

2. What are the different AI Project stages?

Answer – The different AI Project stage are –
a. Problem Scoping
b. Data Acquisition
c. Data Exploration
d. Modeling
e. Evaluation

AI Project Cycle Class 9 Questions and Answers

3. What is Problem Scoping?

Answer – Problem scoping is the process of understanding a problem, determining the various factors that affect the problem, and defining the project’s purpose.

4. How can you identify the problem scoping from the project?

Answer – To identify the problem scoping from the project ae –
a. Understand why the project was started.
b. Define the project’s primary objectives.
c. Outline the project’s work statement.
d. Determine the most important goals.
e. Choose important milestones.
f. Determine the major constraints.
g. Make a list of scope exclusions.

AI Project Cycle Class 9 Questions and Answers

5. What is the 4Ws Problem canvas in AI?

Answer – Who, What, Where, and Why are the 4Ws of Problem Scoping. These four techniques aid in identifying and comprehending the problem.

6. What are the different methods to identify 4Ws Problem canvas?

Answer – The 4 W’s of Problem Scoping are Who, What, Where, and Why.

AI Project Cycle Class 9 Questions and Answers

7. What is the problem statement template?

Answer – Make a summary of what you’ve learnt once you’ve finished the above 4Ws. This summary is known as the problem statement template. This template gathers all of the pertinent information in one location.

8. What is data acquisition?

Answer – Data acquisition is the process of gathering accurate and reliable data to work with. Text, video, photographs, audio, and other types of data can be acquired from a variety of sources, including websites, journals, and newspapers.

AI Project Cycle Class 9 Questions and Answers

9. What is Data?

Answer – Data is a representation of facts or instructions about an entity that can be processed or conveyed by a human or a machine, such as numbers, text, pictures, audio clips, videos, and so on.

10. What is a Dataset?

Answer – A dataset is a tabular system for collecting information. A dataset is a collection of numbers or values relating to a single topic. A dataset is, for example, a group of students’ test results.

AI Project Cycle Class 9 Questions and Answers

11. How many types of dataset available in AI?

Answer – The dataset is divided into two types.

a. Training dataset – A training dataset is a big collection of data that is used to teach a machine learning model. Through training datasets, machine learning algorithms are taught to make decisions or complete tasks. The majority of the dataset is made up of training data .

b. Test dataset – Test data is data that has been clearly identified for use in testing, usually of a computer program. 20% of the data utilized in the tests

12. What are the different ways to collect Acquiring Data?

Answer – The ways to collecting Acquiring data are
a. Surveys
b. Web Scraping
c. Sensors
d. Cameras
e. Observations
f. API (application Program)

AI Project Cycle Class 9 Questions and Answers

13. What is Data Exploration?

Answer – Data analysts use data visualization and statistical methods to express dataset characterizations such as size, number, and correctness in order to better understand the nature of the data.

14. Why is Data Exploration required?

Answer – Exploration aids in the comprehension of a dataset, making it easier to explore and use later. It also aids in the rapid comprehension of data trends and patterns.

AI Project Cycle Class 9 Questions and Answers

15. Why is a Data Visualization Chart required?

Answer – Data visualization charts are graphical representations of data that utilize symbols to tell a story and aid in the comprehension of large amounts of data.

16. What is Artificial Intelligence?

Answer – Artificial intelligence (AI) refers to the simulation of human intelligence in machines that have been programmed to think and act in human-like ways. Artificial Intelligence can also refer to any computer that, like humans, exhibits the ability to learn and solve problems.

AI Project Cycle Class 9 Questions and Answers

17. What is Machine Learning?

Answer – Machine learning is a type of Artificial Intelligence application in which we feed the machine data and let it learn on its own. It’s simply getting a machine to perform a task without being explicitly programmed to do so.

18. What is Deep Learning?

Answer – Deep learning is a branch of artificial intelligence that involves multilayer neural networks. Deep learning examines, learns, and solves problems in the same way that humans do. To train itself, deep learning requires the machine to be trained with a significant amount of data.

AI Project Cycle Class 9 Questions and Answers

19. What do you mean by Rule Based in AI?

Answer – The developer defines the relationship or patterns in data in the rule-based approach to AI modelling. The computer follows the rules or directions of the developer and completes its task correctly.

20. What is data modeling?

Answer – A machine learning model is a computer software that has been trained to recognise patterns from a set of data. The process of developing algorithms, sometimes known as models, that may be trained to create intelligent results is known as AI modelling.

AI Project Cycle Class 9 Questions and Answers

21. What are the different types of AI models?

Answer – The different type of AI Model are –
a. Learning Based
b. Rule Based

22. What is a decision Tree?

Answer – Decision Trees are comparable to Story Speaker in terms of concept. It’s a rule-based AI approach that employs a number of judgments (or rules) to help the computer figure out what an element is.

23. What is Evaluation?

Answer – After a model has been created and trained, it must be thoroughly tested in order to determine its efficiency and performance; this is known as evaluation.

Employability skills Class 9 Notes

• Unit 1 – Communication Skills Class 9 Notes
• Unit 2 – Self-Management Skills Class 9 Notes
• Unit 3 – Basic ICT Skills Class 9 Notes
• Unit 4 – Entrepreneurial Skills Class 9 Notes
• Unit 5 – Green Skills Class 9 Notes

Employability skills Class 9 MCQ

• Unit 1 – Communication Skills Class 9 MCQ
• Unit 2 – Self-Management Skills Class 9 MCQ
• Unit 3 – Basic ICT Skills Class 9 MCQ
• Unit 4 – Entrepreneurial Skillls Class 9 MCQ
• Unit 5 – Green Skills Class 9 MCQ

Employability skills Class 9 Questions and Answers

• Unit 1 – Communication Skills Class 9 Questionns and Answers
• Unit 2 – Self-Management Skills Class 9 Questions and Answers
• Unit 3 – Basic ICT Skills Class 9 Questions and Answers
• Unit 4 – Entrepreneurial Skills Class 9 Questions and Answers
• Unit 5 – Green Skills Class 9 Questions and Answers

Aritificial Intelligence Class 9 Notes

• Unit 1 – Introduction to Artificial Intelligence Class 9 Notes
• Unit 2 – AI Project Cycle Class 9 Notes
• Unit 3 – Neural Network Class 9 Notes
• Unit 4 – Introduction to Python Class 9 Notes
• Unit 4 : Introduction to Tools for AI Class 9 Notes
• Unit 4 : Flow of Control in Python Class 9 Notes
• Unit 4 : Introduction to Packages Python Class 9 Notes

Aritificial Intelligence Class 9 MCQ

• Unit 1 – Introduction to Artificial Intelligence Class 9 MCQ
• Unit 2 – AI Project Cycle Class 9 MCQ
• Unit 3 – Neural Network Class 9 MCQ
• Unit 4 – Introduction to Python Class 9 MCQ

Artificial Intelligence Class 9 Questions and Answers

• Unit 1 – Introduction to Artificial Intelligence Class 9 Questions and Answers
• Unit 2 – AI Project Cycle Class 9 Questions and Answers
• Unit 3 – Neural Network Class 9 Questions and Answers
• Unit 4 – Introduction to Python Class 9 Questions and Answers

Reference Textbook

The above AI Project Cycle Class 9 Questions and Answers was created using the NCERT Book and Study Material accessible on the CBSE ACADEMIC as a reference.

Disclaimer (CBSESkillEducation)- 100% of the questions are taken from the CBSE textbook AI Project Cycle Class 9 Questions and Answers, and our team has tried to collect all the correct QA from the textbook . If you found any suggestion or any error please contact us anuraganand2017@gmail.com.

Teachers and Examiners collaborated to create the AI Project Cycle Class 9 MCQ. All the important MCQs are taken from the NCERT Textbook Artificial Intelligence ( 417 ) class IX.

AI Project Cycle Class 9 MCQ

1. The AI Project Cycle is a ____________ that a company must follow in order to derive value from an AI project and to solve the problem.
a. Step-by-step process 
b. Random process
c. Reverse process
d. None of the above

2. The stages of the AI project cycle are _____________.
a. Problem Scoping & Data Acquisition
b. Data Exploration & Modeling
c. Evaluation
d. All of the above 

3. How you can identify the problem scoping in the project.
a. Understand why the project was started
b. Define the project’s primary objectives
c. Outline the project’s work statement.
d. All of the above 

4. Give the example of a source where you can acquire the data?
a. Sustainable development goals
b. Environment
c. Agriculture
d. All of the above 

AI Project Cycle Class 9 MCQ

5. What are the 4 W’s of problem scoping __________ in AI.
a. Who & What
b. Where
c. Why
d. All of the above 

6. __________ element helps us to understand and categorize who is directly and indirectly affected by the problem.
a. Who 
b. What
c. Where
d. Why

7. ___________ section aids us in analyzing and recognizing the nature of the problem.
a. Who
b. What 
c. Where
d. Why

8. _________ elements help to find where the problem arises.
a. Who
b. What
c. Where
d. Why

9. ___________refers to why we need to address the problem and what the advantages will be for the stakeholders once the problem is solved.
a. Who
b. What
c. Where
d. Why 

AI Project Cycle Class 9 MCQ

10. __________ summarizes all of the important points in one place.
a. Problem statement template 
b. Problem statement document
c. Problem statement file
d. None of the above

11. The method of collecting correct and dependable data to work with is known as ___________.
a. Problem Scoping
b. Data Acquisition 
c. Data Exploration
d. Modeling

12. What is data in AI?
a. Facts
b. Instruction
c. Information
d. All of the above 

13. What are the different types of data __________.
a. Structured Data
b. Unstructured Data
c. Both a) and b) 
d. None of the above

14. If data is easily accessible by humans and program, and easy to read is known as _____________.
a. Structured Data
b. Unstructured Data
c. Both a) and b)
d. None of the above

AI Project Cycle Class 9 MCQ

15. _________ data doesn’t follow traditional data models and is difficult to read, store and manage.
a. Structured Data
b. Unstructured Data
c. Both a) and b)
d. None of the above

16. ________ is a collection of data in tabular format.
a. Dataset
b. Structured Data
c. Unstructured Data
d. None of the above

17. The dataset is divided in two parts ___________.
a. Machine dataset & Model dataset
b. Training dataset & Test dataset
c. Gaolable dataset & local dataset
d. None of the above

18. __________ dataset is a large dataset that is used for teaching a machine learning model.
a. Training dataset 
b. Test dataset
c. Both a) and b)
d. None of the above

19. What is the percentage of data utilized in a training dataset?
a. 50%
b. 20%
c. 80%
d. 100%

AI Project Cycle Class 9 MCQ

20. Data that have been clearly identified for use in tests, usually of a computer program is known as ____________.
a. Training dataset
b. Test dataset
c. Both a) and b)
d. None of the above

21. What is the percentage of data utilized in a test dataset?
a. 50%
b. 20% 
c. 80%
d. 100%

22. What are the different reliable sources to collect the data in AI?
a. Surveys & Web Scraping
b. Sensors & Cameras
c. Observations & API
d. All of the above

23. Web Scripting is a technique for collecting ____________ data from the internet such as news, market research and price tracking.
a. Structured data
b. Unstructured data
c. Scripting data
d. None of the above

24. We can collect visual data with the help of cameras. This data is ___________ data.
a. Structured data
b. Unstructured data
c. Scripting data
d. None of the above

AI Project Cycle Class 9 MCQ

25. A device that detects or measures a physical property is called __________.
a. Sensor
b. API
c. Observation
d. None of the above

26. An __________ is a software interface that enables the interaction between two apps.
a. Sensor
b. API
c. Observation
d. None of the above

27. What is a System Map?
a. Helps to make relation between multiple element
b. Only one elements will be responsible
c. Indicate the relationship using + or –
d. Both a) and c)

28. Data analysts utilize data visualization and statistical tools to convey dataset characterizations, such as ___________.
a. size
b. amount
c. accuracy
d. All of the above

29. Data exploration is a technique used to visualize data in the form of statistical methods or using graphs.
a. Statistical methods
b. Graphical methods
c. Both a) and b)
d. None of the above

AI Project Cycle Class 9 MCQ

30. Data Exploration helps you gain a better understanding of a _________.
a. Dataset
b. Database
c. accuracy
d. None of the above

31. _____________helps to represent graphical data that use symbols to convey a story and help people understand large volumes of information.
a. Dataset
b. Data visualization
c. Data Exploration
d. None of the above

32. A machine that work and react like human is known as ____________.
a. Artificial Intelligence
b. Machine Learning
c. Deep Learning
d. None of the above

33. Machine have a abilities to learn from the experience or data.
a. Artificial Intelligence
b. Machine Learning
c. Deep Learning
d. None of the above

34. It work like structure and function of the brain called artificial neural network.
a. Artificial Intelligence
b. Machine Learning
c. Deep Learning 
d. None of the above

AI Project Cycle Class 9 MCQ

35. _________ is a program that has been trained to recognize patterns using a set of data.
a. AI model 
b. Dataset
c. Visualization
d. None of the above

36. Type of AI model are _____________.
a. Lesson Based and Rood Based
b. Learning Based and Rule Based
c. Machine Learning and Visualization
d. None of the above

AI Project Cycle Class 9 MCQ

37. ___________refers to AI modeling in which the developer hasn’t specified the relationship or patterns in the data.
a. Learning Based
b. Rule Based
c. Decision Tree
d. None of the above

38. After a model has been created and trained, it must be thoroughly tested in order to determine its efficiency and performance; this is known as ___________.
a. Evaluation
b. Learning
c. Decision
d. None of the above

Employability skills Class 9 Notes

• Unit 1 – Communication Skills Class 9 Notes
• Unit 2 – Self-Management Skills Class 9 Notes
• Unit 3 – Basic ICT Skills Class 9 Notes
• Unit 4 – Entrepreneurial Skills Class 9 Notes
• Unit 5 – Green Skills Class 9 Notes

Employability skills Class 9 MCQ

• Unit 1 – Communication Skills Class 9 MCQ
• Unit 2 – Self-Management Skills Class 9 MCQ
• Unit 3 – Basic ICT Skills Class 9 MCQ
• Unit 4 – Entrepreneurial Skillls Class 9 MCQ
• Unit 5 – Green Skills Class 9 MCQ

Employability skills Class 9 Questions and Answers

• Unit 1 – Communication Skills Class 9 Questionns and Answers
• Unit 2 – Self-Management Skills Class 9 Questions and Answers
• Unit 3 – Basic ICT Skills Class 9 Questions and Answers
• Unit 4 – Entrepreneurial Skills Class 9 Questions and Answers
• Unit 5 – Green Skills Class 9 Questions and Answers

Aritificial Intelligence Class 9 Notes

• Unit 1 – Introduction to Artificial Intelligence Class 9 Notes
• Unit 2 – AI Project Cycle Class 9 Notes
• Unit 3 – Neural Network Class 9 Notes
• Unit 4 – Introduction to Python Class 9 Notes
• Unit 4 : Introduction to Tools for AI Class 9 Notes
• Unit 4 : Flow of Control in Python Class 9 Notes
• Unit 4 : Introduction to Packages Python Class 9 Notes

Aritificial Intelligence Class 9 MCQ

• Unit 1 – Introduction to Artificial Intelligence Class 9 MCQ
• Unit 2 – AI Project Cycle Class 9 MCQ
• Unit 3 – Neural Network Class 9 MCQ
• Unit 4 – Introduction to Python Class 9 MCQ

Artificial Intelligence Class 9 Questions and Answers

• Unit 1 – Introduction to Artificial Intelligence Class 9 Questions and Answers
• Unit 2 – AI Project Cycle Class 9 Questions and Answers
• Unit 3 – Neural Network Class 9 Questions and Answers
• Unit 4 – Introduction to Python Class 9 Questions and Answers

Reference Textbook

The above AI Project Cycle Class 9 MCQ was created using the NCERT Book and Study Material accessible on the CBSE ACADEMIC as a reference.

Disclaimer (CBSESkillEducation)- 100% of the questions are taken from the CBSE textbook AI Project Cycle Class 9 MCQ, and our team has tried to collect all the correct MCQs from the textbook . If you found any suggestion or any error please contact us anuraganand2017@gmail.com.

Teachers and Examiners (CBSESkillEduction) collaborated to create the AI Project Cycle Class 9 Notes. All the important Information are taken from the NCERT Textbook Artificial Intelligence (417).

AI Project Cycle Class 9 Notes

The AI Project Cycle is a step-by-step process that a company must follow in order to derive value from an AI project and to solve the problem.

There are five different stage of AI Project Cycle.

Stage of AI Project Cycle

Problem Scoping 

Whenever we begin a new project, we encounter a number of challenges. In fact, we are surrounded with issues! These issues might be minor or major; sometimes we overlook them, and other times we require immediate attention.

To understand a problem, determine the different aspects that affect the problem, and define the project’s goal are problem scoping.

How to Identify the Problem Scoping in AI Project

Follow the following steps to identify the problem scoping from the project –

• Understand why the project was started.
• Define the project’s primary objectives.
• Outline the project’s work statement.
• Determine the most important goals.
• Choose important milestones.
• Determine the major constraints.
• Make a list of scope exclusions.

Acquiring Data from following Source

AI Project Cycle Class 9 Notes

4Ws Problem Canvas

The 4 W’s of Problem Scoping are Who, What, Where, and Why. This 4 W’s helps to identify and understand the problem in a better manner.

a. Who – The “Who” element helps us to understand and categorize who is directly and indirectly affected by the problem, and who are known as Stakeholders.

b. What – The “What” section aids us in analyzing and recognizing the nature of the problem, and you may also gather evidence to establish that the problem you’ve chosen exists under this block.

c. Where – What is the situation, and where does the problem arise.

d. Why – Refers to why we need to address the problem and what the advantages will be for the stakeholders once the problem is solved.

Statement of the Problem Template

After you’ve completed the above 4Ws, make a summary of what you’ve learned. The problem statement template is the name for this summary. This template summarizes all of the important points in one place. So, if the same problem comes again, this statement will make it much easier to fix.

Problem Statement Template with space to fill details according to your Goal:

AI Project Cycle Class 9 Notes

Data Acquisition

The method of collecting correct and dependable data to work with is known as data acquisition. Data can be in the form of text, video, photos, audio, and so on, and it can be gathered from a variety of places such as websites, journals, and newspapers.

What is Data

Data is a representation of facts or instructions about an entity that can be processed or conveyed by a human or a machine, such as numbers, text, pictures, audio clips, videos, and so on.

There is two type of data –

1. Structured Data
2. Unstructured Data

a. Structured Data
When data is in a standardized format, has a well-defined structure, follows a consistent order, and is easily accessible by humans and program. This data is in the form of numbers, characters, special characters etc.

b. Unstructured Data
Unstructured data is information that doesn’t follow traditional data models and is therefore difficult to store and manage. Video, audio, and image files, as well as log files, are all examples of unstructured data.

Dataset

Dataset is a collection of data in tabular format. Dataset contains numbers or values that are related to a specific subject. For example, students’ test scores in a class is a dataset.

The dataset is divided into two parts

a. Training dataset – Training dataset is a large dataset that teaches a machine learning model. Machine learning algorithms are trained to make judgments or perform a task through training datasets. Maximum part of the dataset comes under training data (Usually 80%)

b. Test dataset – Data that has been clearly identified for use in tests, usually of a computer program, is known as test data. 20% of data used in test data

AI Project Cycle Class 9 Notes

Acquiring Data from Reliable Sources

There are six ways to collect data.

a. Surveys
A research method for gathering data from a predetermined sample of respondents in order to get knowledge and insights into a variety of issues.

b. Cameras
We can collect visual data with the help of cameras, this data is unstructured data that can be analyzed via Machine learning.

c. Web Scripting
Web scribing is a technique for collecting structured data from the internet, such as news monitoring, market research, and price tracking.

d. Observation
Some of the information we can gather through attentive observation and monitoring.

e. Sensors
With the help of sensors also we can collect the data. A device that detects or measures a physical property are called sensors, such as biomatrix.

f. Application program interface
An API is a software interface that enables two apps to communicate with one another.

How to create a System Map with example of Water Cycle.

All of the constituents of the Water Cycle are circled in this System Map. With the help of arrows, the map depicts the cause and effect relationships between elements. The arrowhead represents the effect’s direction, while the (+ or -) indicates their relationship. If the arrow with the + sign goes from X to Y, it suggests the two are directly related.

That is, as X rises, Y rises as well, and vice versa. If the arrow, on the other hand, goes with a – sign between X and Y, it signifies that both elements are inversely connected.

This means that while X increases, Y decreases, and vice versa.

Now, it’s your turn to build your own System Map!

AI Project Cycle Class 9 Notes

Data Exploration

In order to better understand the nature of the data, data analysts utilize data visualization and statistical tools to convey dataset characterizations, such as size, amount, and accuracy.

Data exploration is a technique used to visualize data in the form of statistical methods or using graphs.

Why Data Exploration

Exploration helps you gain a better understanding of a dataset, making it easier to explore and use it later. It also helps to quickly understand the data’s trends, and patterns.

About Data Visualization Chart

Data visualization charts are graphical representations of data that use symbols to convey a story and help people understand large volumes of information.

The following are some of the most frequent data visualization chart and graph formats:

a. Column Chart – A column chart is a basic Visualization chart that uses vertical columns to represent data series. Because column lengths are easy to compare, column charts are an effective approach to demonstrate the changes in the data.

b. Bar Chart – A bar chart is a visual representation of category data. The data is displayed in a bar chart with multiple bars, each representing a different category.

AI Project Cycle Class 9 Notes

Modelling

AL, ML & DL

Venn Diagram of AI

Artificial Intelligence

Artificial intelligence (AI) is the simulation of human intelligence in robots that have been trained to think and act like humans. The term can also refer to any machine that demonstrates, like humans, the ability to learn and solve the problem is Artificial Intelligence.

Machine Learning

Machine learning is a part of an Artificial Intelligence application in which we give data to the machine and allow them to learn for themselves. It’s essentially getting a machine to accomplish something without being specifically programmed to do so.

Deep Learning

Deep learning is a part of Artificial Intelligence that uses neural networks with multilayer. Deep learning analyzes the data, learns the data and solves the problem the same as a human. Deep learning requires the machine to be educated with a large quantity of data in order to train itself.

Rule Based

The rule-based approach to AI modeling is when the developer defines the relationship or patterns in data. The machine follows the developer’s rules or instructions and completes its job properly.

What is Modeling

An AI model is a program that has been trained to recognize patterns using a set of data. AI modeling is the process of creating algorithms, also known as models, that may be educated to produce intelligent results. This is the process of programming code to create a machine artificially.

AI Project Cycle Class 9 Notes

Rule Based AI Model (Decision Tree)

Learning Based Approach

Refers to AI modeling in which the developer hasn’t specified the relationship or patterns in the data. Random data is provided to the computer in this method, and the system is left to figure out patterns and trends from it. When the data is unlabeled and too random for a human to make sense of, this method is usually used.

Decision Tree in AI

The concept of Decision Trees is similar to that of Story Speaker. It’s a rule-based AI model that uses numerous judgments (or rules) to assist the machine in determining what an element is. The following is the basic structure of a decision tree:

Points to Remember

When creating Decision Trees, one should carefully examine the dataset provided and try to determine what pattern the output leaf follows. Try picking one output and figuring out the common links that all similar outputs have based on it.

When building a decision tree, it’s common for the dataset to have redundant material that’s of no use. As a result, you should make a list of the parameters that directly affect the output and use only those when designing a decision tree.

For a single dataset, there may be several decision trees that lead to correct prediction. The most straightforward option should be selected.

AI Project Cycle Class 9 Notes

Evaluation

After a model has been created and trained, it must be thoroughly tested in order to determine its efficiency and performance; this is known as evaluation.

Note – You will learn evaluation in class 10

Employability skills Class 9 Notes

• Unit 1 – Communication Skills Class 9 Notes
• Unit 2 – Self-Management Skills Class 9 Notes
• Unit 3 – Basic ICT Skills Class 9 Notes
• Unit 4 – Entrepreneurial Skills Class 9 Notes
• Unit 5 – Green Skills Class 9 Notes

Employability skills Class 9 MCQ

• Unit 1 – Communication Skills Class 9 MCQ
• Unit 2 – Self-Management Skills Class 9 MCQ
• Unit 3 – Basic ICT Skills Class 9 MCQ
• Unit 4 – Entrepreneurial Skillls Class 9 MCQ
• Unit 5 – Green Skills Class 9 MCQ

Employability skills Class 9 Questions and Answers

• Unit 1 – Communication Skills Class 9 Questionns and Answers
• Unit 2 – Self-Management Skills Class 9 Questions and Answers
• Unit 3 – Basic ICT Skills Class 9 Questions and Answers
• Unit 4 – Entrepreneurial Skills Class 9 Questions and Answers
• Unit 5 – Green Skills Class 9 Questions and Answers

Aritificial Intelligence Class 9 Notes

• Unit 1 – Introduction to Artificial Intelligence Class 9 Notes
• Unit 2 – AI Project Cycle Class 9 Notes
• Unit 3 – Neural Network Class 9 Notes
• Unit 4 – Introduction to Python Class 9 Notes
• Unit 4 : Introduction to Tools for AI Class 9 Notes
• Unit 4 : Flow of Control in Python Class 9 Notes
• Unit 4 : Introduction to Packages Python Class 9 Notes

Aritificial Intelligence Class 9 MCQ

• Unit 1 – Introduction to Artificial Intelligence Class 9 MCQ
• Unit 2 – AI Project Cycle Class 9 MCQ
• Unit 3 – Neural Network Class 9 MCQ
• Unit 4 – Introduction to Python Class 9 MCQ

Artificial Intelligence Class 9 Questions and Answers

• Unit 1 – Introduction to Artificial Intelligence Class 9 Questions and Answers
• Unit 2 – AI Project Cycle Class 9 Questions and Answers
• Unit 3 – Neural Network Class 9 Questions and Answers
• Unit 4 – Introduction to Python Class 9 Questions and Answers

Reference Textbook

The above AI Project Cycle Class 9 Notes Notes was created using the NCERT Book and Study Material accessible on the CBSE ACADEMIC as a reference.

Disclaimer – 100% of the questions are taken from the CBSE textbook AI Project Cycle Class 9 Notes, our team has tried to collect all the correct Information from the textbook . If you found any suggestion or any error please contact us anuraganand2017@gmail.com.

Teachers and Examiners collaborated to create the Artificial Intelligence Class 9 Chapter 1 Solutions. All the important QA are taken from the NCERT Textbook Artificial Intelligence ( 417 ) class IX.

Artificial Intelligence Class 9 Chapter 1 Solutions

1. What is Artificial Intelligence?

Answer – Artificial intelligence (AI) is a branch of computer science that focuses on the development of intelligent machines that function and react similarly to humans.

2. What is an artificial intelligence Neural Networks?

Answer – In the domains of AI, machine learning, and deep learning, neural networks simulate the function of the human brain, allowing computer program to recognize patterns and solve common problems.

Artificial Intelligence Class 9 Chapter 1 Solutions

3. What are the various areas where Artificial Intelligence can be used?

Answer – The areas where Artificial Intelligence can be used –

• Healthcare and Medical Imaging Analysis
• Virtual Assistant or Chatbots
• Security and Surveillance
• Agriculture and Farming
• Retail, Shopping and Fashion
• Manufacturing and Production
• Sports Analytics and Activities
• Self-driving Cars or Autonomous Vehicles

4. The most popular programming language for AI?

Answer – The most popular programming language for AI is Python.

5. When the artificial Intelligence was coined?

Answer – Artificial Intelligence formally founded in 1956, when the term “Artificial Intelligence” was coined at a conference at Dartmouth College in Hanover, New Hampshire.

Artificial Intelligence Class 9 Chapter 1 Solutions

6. What do you mean by Machine Learning?

Answer – Machine learning is an artificial intelligence area that allows computers to learn and improve without having to be explicitly programmed. Machine learning is the process of developing computer program that can access data and learn on their own.

7. What is Natural Language Processing?

Answer – Natural language processing (NLP) is a branch of artificial intelligence (AI) that helps computers recognize how people write and communicate.

8. What is Expert System?

Answer – An expert system is a software program that can deal with difficult problems and make choices in the same way as a human expert can.

Artificial Intelligence Class 9 Chapter 1 Solutions

9. What is Computer Vision?

Answer – Computer vision is a subset of artificial intelligence (AI) that enables computers and systems to extract usable information from digital pictures, videos, and other visual inputs, as well as to take actions or make recommendations based on that information.

10. What is AI Speech technology?

Answer – This Speech technology can now translate voice messages into text. It can also recognize a person based by their spoken orders.

11. What are the different Applications of Artificial Intelligence?

Answer – The different Applications of Artificial Intelligence are –
a. AI Application in E-Commerce
b. Artificial Intelligence in Automobiles
c. Artificial Intelligence in Social Media
d. Artificial Intelligence in Agriculture
e. Artificial Intelligence in Robotics

Artificial Intelligence Class 9 Chapter 1 Solutions

12. Give any three example of Artificial Intelligence Domain?

Answer – There is a three type of domain in Artificial Intelligence.
a. Data Science (Data for AI)
b. Natural Language Procession (NLP)
c. Computer Vision (CV)

13. What do you mean by Data Science?

Answer – Data Science is the process of transforming a raw dataset into useful information.

14. What are the different Real World Application in AI?

Answer – The different real world application in AI is –
a. Google Maps and Ride
b. Face detection
c. Text editors on autocorrect and autocomplete

Artificial Intelligence Class 9 Chapter 1 Solutions

15. What are the advantages of Smart Home?

Answer – Advantages of Smart Home are –

• Smart Home provide more comfort
• Smart Home improve Security
• Smart Home saves energy
• Smart Home helps to save your money
• Smart Home means more free time

16. What is Smart City?

Answer – The Smart Cities Mission’s purpose is to promote economic growth and improve people’s quality of life by promoting local area development and leveraging technology, particularly smart technology.

17. What are the Advantages of Smart City?

Answer – The advantages of Smart City are –
Improved Infrastructure
Safer Communication
More Jobs Opportunities
Decrease of Crime

Artificial Intelligence Class 9 Chapter 1 Solutions

18. What is sustainable development?

Answer – Sustainable development is defined as development that does not compromise future generations’ ability to meet their requirements.
The Brundtland report first mentioned sustainable development in 1987. This was a warning to all countries about the effects of globalization and economic growth on the environment.

19. How many goals are there in Sustainable Development?

Answer – There are 17 goals in sustainable Development –

1. Zero Hunger
2. No Poverty
3. Good Health and Well-Being
4. Quality Education
5. Climate action
6. Industry Innovation and Infrastructure
7. Gender Equality
8. Clean Water and Sanitation
9. Affordable and clean energy
10. Sustainable cities and communities
11. Decent work and economic growth
12. Reduce Inequalities
13. Responsible consumption and production
14. Life on land
15. Life below water
16. Partnerships for the goals

Artificial Intelligence Class 9 Chapter 1 Solutions

20. Give any two example of AI solutions to Social Issues?

Answer – The two example of AI solutions to Social Issues are –
a. Disaster Awareness and Prediction
Huge companies, such as Google, are concentrating on flood protection, employing artificial intelligence to forecast high-risk areas and alerting citizens.

b. AI in Agriculture
Artificial intelligence is used in smart farming to improve overall harvest quality and accuracy. Plant disease, pests, and inadequate agricultural nutrition can all be detected with AI technology. Artificial intelligence sensors can detect and target plants, then select the most effective herbicide to spray in the region.

Artificial Intelligence Class 9 Chapter 1 Solutions

21. What are the different career opportunity in Artificial Intelligence.

Answer – The career opportunity in Artificial Intelligence are –
1. Data Analytics
2. Natural Language Processing
3. Robotic Scientist
4. Research Scientist
5. Researcher
6. Software Engineer

Artificial Intelligence Class 9 Chapter 1 Solutions

22. What different Skills required in AI-related Job?

Answer- The Skills required for AI-related jobs are –

• Required Training to become a expertise in the field of Artificial Intelligence
• Good knowledge of Math and Science related to AI
• Required Programming Languages like Python, Java, Web related language etc.
• Linear algebra and statistics
• Signal processing techniques
• Neural network architectures

23. What are the different ethical challenges in Artificial Intelligence?

Answer – The ethical challenges in Artificial Intelligence are –
Cost to Innovation
Lack of quality data
Problems of Integrity
Lack of accuracy of data
Bias and discrimination

Employability skills Class 9 Notes

• Unit 1 – Communication Skills Class 9 Notes
• Unit 2 – Self-Management Skills Class 9 Notes
• Unit 3 – Basic ICT Skills Class 9 Notes
• Unit 4 – Entrepreneurial Skills Class 9 Notes
• Unit 5 – Green Skills Class 9 Notes

Employability skills Class 9 MCQ

• Unit 1 – Communication Skills Class 9 MCQ
• Unit 2 – Self-Management Skills Class 9 MCQ
• Unit 3 – Basic ICT Skills Class 9 MCQ
• Unit 4 – Entrepreneurial Skillls Class 9 MCQ
• Unit 5 – Green Skills Class 9 MCQ

Employability skills Class 9 Questions and Answers

• Unit 1 – Communication Skills Class 9 Questionns and Answers
• Unit 2 – Self-Management Skills Class 9 Questions and Answers
• Unit 3 – Basic ICT Skills Class 9 Questions and Answers
• Unit 4 – Entrepreneurial Skills Class 9 Questions and Answers
• Unit 5 – Green Skills Class 9 Questions and Answers

Aritificial Intelligence Class 9 Notes

• Unit 1 – Introduction to Artificial Intelligence Class 9 Notes
• Unit 2 – AI Project Cycle Class 9 Notes
• Unit 3 – Neural Network Class 9 Notes
• Unit 4 – Introduction to Python Class 9 Notes
• Unit 4 : Introduction to Tools for AI Class 9 Notes
• Unit 4 : Flow of Control in Python Class 9 Notes
• Unit 4 : Introduction to Packages Python Class 9 Notes

Aritificial Intelligence Class 9 MCQ

• Unit 1 – Introduction to Artificial Intelligence Class 9 MCQ
• Unit 2 – AI Project Cycle Class 9 MCQ
• Unit 3 – Neural Network Class 9 MCQ
• Unit 4 – Introduction to Python Class 9 MCQ

Artificial Intelligence Class 9 Questions and Answers

• Unit 1 – Introduction to Artificial Intelligence Class 9 Questions and Answers
• Unit 2 – AI Project Cycle Class 9 Questions and Answers
• Unit 3 – Neural Network Class 9 Questions and Answers
• Unit 4 – Introduction to Python Class 9 Questions and Answers

Reference Textbook

The above Artificial Intelligence Class 9 Chapter 1 Solutions was created using the NCERT Book and Study Material accessible on the CBSE ACADEMIC as a reference.

Disclaimer (CBSESkillEducation)- 100% of the questions are taken from the CBSE textbook Artificial Intelligence Class 9 Chapter 1 Solutions, and our team has tried to collect all the correct QA from the textbook . If you found any suggestion or any error please contact us anuraganand2017@gmail.com.

Teachers and Examiners collaborated to create the Introduction to Artificial Intelligence Class 9 MCQ. All the important MCQs are taken from the NCERT Textbook Artificial Intelligence ( 417 ) class IX.

Introduction to Artificial Intelligence Class 9 MCQ

1. ___________ is the ability of machines to do cognitive tasks such as thinking, perceiving, learning, problem solving, and decision making.
a. Artificial Intelligence
b. Nero Science
c. Data package
d. None of the above

2. What is the full form of “AI”?
a. Artificially Intelligent
b. Artificially Intelligence
c. Artificial Intelligence
d. Advanced Intelligence

Introduction to Artificial Intelligence Class 9 MCQ

3. Artificial Intelligence is about_____.
a. Playing a game on Computer
b. Making a machine Intelligent
c. Programming on Machine with your Own Intelligence
d. Putting your intelligence in Machine

4. Who is the “Father of Artificial Intelligence”?
a. Fisher Ada
b. Alan Turing
c. John McCarthy
d. Allen Newell

Introduction to Artificial Intelligence Class 9 MCQ

5. Artificial Intelligence’s applications are_________.
a. Expert Systems
b. Gaming
c. Vision Systems
d. All of the above

6. The_________ approach was designed to judge whether a machine could or could not display artificial intelligence.
a. Boolean Algebra
b. Turing Test
c. Logarithm
d. Algorithm

7. When was the AI Dartmouth conference?
a. 1956
b. 1966
c. 1972
d. 1980

8. Artificial Intelligence is divided into which of the following branches?
a. Machine Learning
b. Cyber forensics
c. Full-Stack Developer
d. Network Design

9. The important principle that artificial intelligence embraces is holistic inclusive and progressive development in immersive ways by __________.
a. Problem solving
b. Creative thinking
c. Critically Analyzing data
d. All of the above

Introduction to Artificial Intelligence Class 9 MCQ

10. Identify the pedagogy of AI
a. Activity Based
b. Experiential learning
c. Inquiry Based learning
d. All of the above

11. Which one of the following is an application of AI?
a. Remote controlled Drone
b. Self-Driving Car
c. Self-Service Kiosk
d. Self-Watering Plant System

Introduction to Artificial Intelligence Class 9 MCQ

12. This language is easy to learn and is one of the most popular language for AI today:
a. C++
b. Python
c. Ruby
d. Java

13. Which of the following is not a stage in the AI Project Cycle:
a. Problem Scoping
b. Data Acquisition
c. Data Exploration
d. Prototyping

14. This field is enabling computers to identify and process images like humans do:
a. Face Recognition
b. Model-view-controller
c. Computer Vision
d. Eye-in-Hand System

Introduction to Artificial Intelligence Class 9 MCQ

15. What does NLP stand for in AI?
a. Neutral Learning Projection
b. Neuro-Linguistic Programming
c. Natural Language Processing
d. Neural Logic Presentation

16. This is a program that allows the computer to simulate conversation with a human being:
a. Speech Application Program Interface
b. Chatbot
c. Voice Recognition
d. Speech Recognition

Introduction to Artificial Intelligence Class 9 MCQ

17. This is a system of Programs and Data-Structures that mimics the operation of the human brain:
a. Intelligent Network
b. Decision Support System
c. Neural Network
d. Genetic Programming

18. Where is the Decision tree used?
a. Classification Problem
b. Regression Problem
c. Clustering Problem
d. Dimensionality Reduction

19. What does a model. Add (dense(32, input_shape=(784))) do?
a. It adds an input layer
b. It adds a hidden layer
c. It adds an output layer
d. It adds a dense layer

Introduction to Artificial Intelligence Class 9 MCQ

20. Natural language processing has two subfields, namely:
a. algorithmic and heuristic
b. time and motion
c. understanding and generation
d. symbolic and numeric

21. The first Chatboat “ELIZA” introduced in the year of _________.
a. 1988
b. 1955
c. 1966
d. 1990

22. In the year of _________, The IBM Deep blue “First computer to beat a world chess championship”
a. 1988
b. 1955
c. 1997
d. 1990

23. _________ is a series of autonomous robotic vacuum cleaners used in Home.
a. Roomba
b. Expert System
c. Deep Blue
d. Goostman

24. In which year google Introduce AI is their application.
a. 2008
b. 2012
c. 2014
d. 2016

Introduction to Artificial Intelligence Class 9 MCQ

25. _____________ is a branch of artificial intelligence that allows computers to learn and develop without being explicitly programmed.
a. Machine Learning
b. Natural Language Processing
c. Expert System
d. Computer Vision

26. Machine Learning can be used to address difficult problems like detecting ____________
a. credit card fraud
b. enabling self-driving automobiles
c. detecting and recognizing faces
d. All of the above

27. Natural language processing is an area of artificial intelligence that focuses on assisting computers in understanding
a. How humans write and communicate
b. How humans work in organization
c. How humans Use a AI Device
d. None of the above

Introduction to Artificial Intelligence Class 9 MCQ

28. _________is a computer software that can handle complex issues and make decisions in the same way as a human can.
a. Machine Learning
b. Natural Language Processing
c. Expert System
d. Computer Vision

29. _________ device can do activities without the need of human interaction.
a. Robots
b. Planner
c. AI
d. None of the above

Introduction to Artificial Intelligence Class 9 MCQ

30. _____________ aid in the enhancement of the online buying experience.
a. Virtual Shopping Assistants
b. Chatbots
c. Both a) and b)
d. None of the above

31. What are the most serious difficulties that E-Commerce businesses face are ____________.
a. Credit Card Fraud
b. Fraudulent Reviews
c. Both a) and b)
d. None of the above

Introduction to Artificial Intelligence Class 9 MCQ

32. Self-driving automobiles are built using artificial intelligence. To drive the vehicle, AI can be combined with the___________.
a. Camera
b. Radar
c. GPS & Control Signals
d. All of the above

33. Facebook uses the technique known as ___________, this technique translates the post from one language to another language.
a. DeepText
b. Language converter
c. Converter
d. None of the above

34. Twitter uses AI technology in their application to solve the _____________ problem.
a. Fraud detection
b. Propaganda Removal
c. Remove hateful content
d. All of the above

Introduction to Artificial Intelligence Class 9 MCQ

35. With the help of AI the farmer can identify defects and nutrient deficiencies in the soil with the help of _________.
a. machine learning applications
b. Natural Language Processing
c. Expert System
d. Computer Vision

36. Which one is the correct domain available in Artificial Intelligence.
a. Data Science
b. Natural Language Processing
c. Computer Vision
d. All of the above

37. The process of converting a raw dataset into valuable knowledge is known as ___________.
a. Data Science
b. Natural Language Processing
c. Computer Vision
d. All of the above

Introduction to Artificial Intelligence Class 9 MCQ

38. ____________ is an AI game based on data science.
a. Rock, Paper, Scissors
b. Akinator with alexa
c. Emoji Scavenger
d. None of the above

39. ___________is a free Amazon Echo app that uses a series of questions to figure out which character you’re thinking of
a. Rock, Paper, Scissors
b. Akinator with alexa
c. Emoji Scavenger
d. None of the above

Introduction to Artificial Intelligence Class 9 MCQ

40. ___________ allows computers and systems to extract useful information from digital photos, videos, and other visual inputs.
a. Data Science
b. Natural Language Processing
c. Computer Vision
d. All of the above

41. ___________is a web-based service that provides accurate data on geographic regions and locations all over the world.
a. Google Bot
b. Google Map
c. Google Class
d. None of the above

42. A ____________ is a flexible house setup in which appliances and devices may be managed remotely using a mobile or other networked device from anywhere with an internet connection.
a. Smart Home
b. Smart City
c. Smart Class
d. None of the above

Introduction to Artificial Intelligence Class 9 MCQ

43. What are the advantages of Smart Home?
a. Smart Home provide more comfort
b. Smart Home Saves Energy
c. Smart Home Improve Security
d. All of the above

44. In 1987 the first time sustainable development appeared in the __________.
a. Brundtland Report
b. British Report
c. World Report
d. None of the above

Introduction to Artificial Intelligence Class 9 MCQ

45. There are _________ goals in sustainable development which were introduced in 2015.
a. 16
b. 17
c. 18
d. 19

46. In which area AI will improve and give the solution to Social issues.
a. Disaster Awareness and Prediction
b. Wildlife Conservation
c. In Agriculture
d. All of the above

47. Give the example of career opportunities in Artificial Intelligence.
a. Data Analytics
b. Machine Learning Engineer
c. Software Engineer
d. All of the above

48. What are the companies that make use of AI
a. Google
b. Apple
c. Amazon
d. All of the above

Introduction to Artificial Intelligence Class 9 MCQ

49. What skills required  when you are working as AI professional.
a. Training to become a expertise
b. Good knowledge of Math and Science
c. Required Programming Languages
d. All of the above

50. Ethical Challenges in Artificial Intelligence?
a. Cost to Innovation
b. Lack of quality data
c. Bias and discrimination
d. All of the above

Employability skills Class 9 Notes

• Unit 1 – Communication Skills Class 9 Notes
• Unit 2 – Self-Management Skills Class 9 Notes
• Unit 3 – Basic ICT Skills Class 9 Notes
• Unit 4 – Entrepreneurial Skills Class 9 Notes
• Unit 5 – Green Skills Class 9 Notes

Employability skills Class 9 MCQ

• Unit 1 – Communication Skills Class 9 MCQ
• Unit 2 – Self-Management Skills Class 9 MCQ
• Unit 3 – Basic ICT Skills Class 9 MCQ
• Unit 4 – Entrepreneurial Skillls Class 9 MCQ
• Unit 5 – Green Skills Class 9 MCQ

Employability skills Class 9 Questions and Answers

• Unit 1 – Communication Skills Class 9 Questionns and Answers
• Unit 2 – Self-Management Skills Class 9 Questions and Answers
• Unit 3 – Basic ICT Skills Class 9 Questions and Answers
• Unit 4 – Entrepreneurial Skills Class 9 Questions and Answers
• Unit 5 – Green Skills Class 9 Questions and Answers

Aritificial Intelligence Class 9 Notes

• Unit 1 – Introduction to Artificial Intelligence Class 9 Notes
• Unit 2 – AI Project Cycle Class 9 Notes
• Unit 3 – Neural Network Class 9 Notes
• Unit 4 – Introduction to Python Class 9 Notes
• Unit 4 : Introduction to Tools for AI Class 9 Notes
• Unit 4 : Flow of Control in Python Class 9 Notes
• Unit 4 : Introduction to Packages Python Class 9 Notes

Aritificial Intelligence Class 9 MCQ

• Unit 1 – Introduction to Artificial Intelligence Class 9 MCQ
• Unit 2 – AI Project Cycle Class 9 MCQ
• Unit 3 – Neural Network Class 9 MCQ
• Unit 4 – Introduction to Python Class 9 MCQ

Artificial Intelligence Class 9 Questions and Answers

• Unit 1 – Introduction to Artificial Intelligence Class 9 Questions and Answers
• Unit 2 – AI Project Cycle Class 9 Questions and Answers
• Unit 3 – Neural Network Class 9 Questions and Answers
• Unit 4 – Introduction to Python Class 9 Questions and Answers

Reference Textbook

The above Introduction to Artificial Intelligence Class 9 MCQ was created using the NCERT Book and Study Material accessible on the CBSE ACADEMIC as a reference.

Disclaimer (CBSESkillEducation)- 100% of the questions are taken from the CBSE textbook Introduction to Artificial Intelligence Class 9 MCQ, and our team has tried to collect all the correct MCQs from the textbook . If you found any suggestion or any error please contact us anuraganand2017@gmail.com.

Teachers and Examiners (CBSESkillEduction) collaborated to create the Introduction to Artificial Intelligence Class 9 Notes. All the important Information are taken from the NCERT Textbook Artificial Intelligence (417).

Introduction to Artificial Intelligence Class 9

Introduction to Artificial Intelligence

Artificial Intelligence is formed by combining the two words artificial and intelligence.
a. Artificial – Artificial refers to something created or produced by humans rather than existing naturally
b. Intelligence – The ability to acquire and use knowledge and skills is referred to as intelligence.

Artificial Intelligence Definition  

Artificial Intelligence (AI) is the ability of machines to do cognitive tasks such as thinking, perceiving, learning, problem solving, and decision making. It is based on how individuals use their brains to observe, learn, figure out, and make decisions.

Artificial Intelligence has been defined in a variety of ways by various organizations.

Artificial Intelligence NITI Aayog

The ability of machines to execute cognitive functions such as thinking, perceiving, learning, problem solving, and decision making is referred to as artificial intelligence (AI).

World Economic Forum Artificial Intelligence

The software engine that propels the Fourth Industrial Revolution is artificial intelligence (AI). It has already had an impact on people’s lives, businesses, and political processes. It will soon be driving automobiles, stocking warehouses, and caring for the young and elderly in its embodied form of robots. It holds the prospect of resolving some of society’s most serious problems.

European Artificial Intelligence

AI isn’t a well-defined technology, and there isn’t a single description that everyone agrees on. It’s more of a catch-all word for data analysis and pattern detection tools.

Artificial Intelligence Encyclopedia Britannica

Artificial intelligence (AI) refers to a digital computer’s or a computer-controlled robot’s ability to do tasks normally performed by intelligent beings.

Introduction to Artificial Intelligence Class 9

History of Artificial Intelligence

Artificial Intelligence formally founded in 1956, when the term “Artificial Intelligence” was coined at a conference at Dartmouth College in Hanover, New Hampshire.
The phrase “artificial intelligence” was created by John McCarthy, who also hosted the first AI conference.

1. 1956 – Birth of AI Dartmouth Conference
2. 1966 – First Chatbot “ELIZA”
3. 1972 – First Intelligence “Robot WABOT – 1”
4. 1974 – 1980 : First AI winer1980 : Expert System
5. 1987 – 1993 : Second AI Winer
6. 1997 – IBM Deep blue “First computer to beat a world chess champion”
7. 2002 – AI in Home “Roomba”
8. 2011 – IBM Watson “Wins a Quiz show”
9. 2012 – Google Introduce AI in there application
10. 2014 – Chatbot Eugene Goostman “Wines a Turing test
11. 2015 – Amazon Echo

Introduction to Artificial Intelligence Class 9

Role of AI in Education

The use of technology in education is changing the way we teach and learn all across the world. Artificial Intelligence (AI) is one of the technological innovations that may be used to adapt the learning experience of different learning groups, teachers, and tutors.

The picture below displays some of the most fundamental AI competencies –

What is Machine Learning

Machine learning is a branch of artificial intelligence that allows computers to learn and develop without being explicitly programmed. Machine learning is concerned with the creation of computer program that can access data and learn for themselves.

Machine Learning can be used to address difficult problems like detecting credit card fraud, enabling self-driving automobiles, and detecting and recognizing faces.

What is Natural Language Processing

Natural language processing (NLP) is an area of artificial intelligence (AI) that focuses on assisting computers in understanding how humans write and communicate. This is a difficult task because of the large amount of unstructured data involved.

What is Expert System

An expert system is a computer software that can handle complex issues and make decisions in the same way as a human expert can.

What is Vision in AI

Computer vision is a branch of artificial intelligence (AI) that allows computers and systems to extract useful information from digital photos, videos, and other visual inputs, as well as to conduct actions or make recommendations based on that data.

What is Speech Recognition in AI

Voice messages can now be converted to text using this Speech technology. It’s also capable of recognizing a person based on their voiced commands.

What is Planning in AI

In Artificial Intelligence, planning refers to the decision-making duties carried out by robots or computer programmes in order to attain a given goal.

What is Robotics

Robotics is the production of robots that can do activities without the need of human interaction, whereas AI is the process of systems imitating the human mind to make judgments and ‘learn.’

Introduction to Artificial Intelligence Class 9

ExCIT

ExCITE was the result of our brainstorming. ExCITE is a technology-agnostic evaluation methodology for Artificial Intelligence solutions that focuses on transparency.

Applications of Artificial Intelligence

AI Application in E Commerce

a. Personalized Shopping – Artificial Intelligence (AI) is used to develop recommendation engines that help you engage with your customers more effectively. These suggestions are based on their previous browsing behavior, preferences, and interests.

b. AI-powered Assistants – Virtual shopping assistants and chatbots aid in the enhancement of the online buying experience.

c. Fraud Prevention – Two of the most serious difficulties that E-Commerce businesses face are credit card fraud and fraudulent reviews.

Artificial Intelligence in Automobiles

Self-driving automobiles are built using artificial intelligence. To drive the vehicle, AI can be combined with the camera, radar, cloud services, GPS, and control signals.

Artificial Intelligence in Social Media

Many of the social media sites use a AI technology in Social Media

a. Facebook – Artificial Intelligence uses the technique known as DeepText. DeepText automatically translates the post from one language to another language.

b. Twitter – Twitter uses AI for fraud detection, propaganda removal, and to remove hateful content.

Artificial Intelligence in Agriculture

With the help of AI the farmer can identify defects and nutrient deficiencies in the soil with the help of machine learning applications

Artificial Intelligence in Robotics

Another industry where artificial intelligence applications are widely used is robotics. AI-powered robots use real-time updates to detect obstructions in their path and instantaneously arrange their route.

Introduction to Artificial Intelligence Class 9

Three Domains of Artificial Intelligence

There are three types of domain in Artificial Intelligence.

1. Data Science (Data for AI)
2. Natural Language Processing (NLP)
3. Computer Vision (CV)

1. Data Science (Data for AI) –

The process of converting a raw dataset into valuable knowledge is known as Data Science. Nowadays Data Science is an important part of an Industry. Data science is an AI domain concerned with data systems and processes, in which the system collects a large amount of data, maintains sets of data, and extracts meaning from them.

AI Games related to Data Science

Rock, Paper, Scissors AI Game (Based on Data Science)

Rock, Paper, Scissors is an easy game to play. Each player chooses one of the three things (typically by creating the appropriate hand shape on three counts!) and the following rules are used to determine who won that round:

• Paper wraps (beats) Rock
• Scissors cut (beat) Paper
• Rock blunts (beats) Scissors

The purpose of the game is to guess your opponent’s choice and select the proper object to defeat them.

Game link (Play in computer)
https://rps-ai-game.herokuapp.com

2. Natural Language Processing (NLP)

Natural language processing (NLP) is a branch of artificial intelligence. Natural language Processing has the ability to understand text and spoken words in the same manner that humans can.

AI Games related to Natural language Processing (NLP)

• Akinator with alexa AI Game (Based on Natural Language Processing)
• Akinator is a free Amazon Echo app that uses a series of questions to figure out which character you’re thinking of.
• You can ask the app to guess the identity of a real or imaginary individual.

Game link (Play in mobile phone)
https://play.google.com/store/apps/details?id=com.digidust.elokence.akinator.freemium&hl=en_IN&gl=US

3. Computer Vision (CV)

Computer vision allows computers and systems to extract useful information from digital photos, videos, and other visual inputs. The goal of Computer Vision is to take necessary action after identifying an object or person in a digital image.

AI Games related to Computer Vision

Emoji Scavenger Hunt (Based on Computer Vision)

Emoji Scavenger Hunt is a project that uses neural networks and your phone’s camera to detect real-world counterparts of the emoticons we use on a daily basis.

Game link

Website link – https://emojiscavengerhunt.withgoogle.com/

Reverse Image Search (Based on Computer Vision)

Google’s picture search is presently only available on desktop computers. If a friend has sent an image to you on WhatsApp or Facebook that you want to verify, you’ll need to first copy the image to a desktop and then run a reverse image search.

Website link –
https://www.labnol.org/reverse/

Introduction to Artificial Intelligence Class 9

Relate

Real World Application

1. Google Maps and Ride – hailing application
Google Maps is a web-based service that provides accurate data on geographic regions and locations all over the world. Google has added new features of google ride which compare ride services and their pricing with alternative modes of transportation, such as public transit or walking, in the Google Maps app.

2. Face detection (Virtual Filter, Face ID unlocking)
Biometrics are used in a facial recognition system to map facial traits from a photograph or video. To identify a match, it compares the information to a database of known faces. Facial recognition can aid in the verification of a person’s identification, but it also raises concerns about privacy.

3. Text editors on autocorrect and autocomplete

Autocorrect: This feature corrects any spelling mistakes made while typing.

Autocomplete: If a term has already been used, this function provides suggestions for automatically finishing it. If you type ‘msword’ once, it will try to complete the sentence by displaying msword on the next line if you type ‘ms’.

Introduction to Artificial Intelligence Class 9

What is Smart Home

A smart home is a flexible house setup in which appliances and devices may be managed remotely using a mobile or other networked device from anywhere with an internet connection.

Advantages of Smart Home

1. Smart Home provide more comfort
2. Smart Home improve Security
3. Smart Home saves energy
4. Smart Home helps to save your money
5. Smart Home means more free time

Disadvantages of Smart Home

1. Cost
2. Always depends on Internet

What is Smart City

The Smart Cities Mission’s goal is to promote economic growth and improve people’s quality of life by facilitating local area development and utilizing technology, particularly technology that leads to Smart results.

Advantages of Smart City

1. Improved Infrastructure
2. Safer Communication
3. More Jobs Opportunities
4. Decrease of Crime

Disadvantages of Smart City

1. Concerns about data security and privacy
2. Excess network trust
3. It’s difficult to get the financial model for implementation out there.

Introduction to Artificial Intelligence Class 9

Purpose

Role of AI in Sustainable Development

What is Sustainable Development

Sustainable development is the development which doesn’t compromise the capacity of the future generation to satisfy their needs.
In 1987 the first time sustainable development appeared in the Brundtland report. This was a warning to all countries regarding environmental consequences, globalization and economic growth.
Sustainable Development goals are also known as Global goals. There are 17 goals in sustainable development which were introduced in 2015.

There are total 17 Sustainable Development Goals are:

1. Zero Hunger
Food supply is aided by AI throughout the supply network, from manufacturing to transportation and distribution.

2. No Poverty
Artificial intelligence has the potential to help reduce the number of individuals driven into poverty as a result of natural disasters.

3. Good Health and Well-Being
Doctors and radiologists are collaborating to identify ways to use AI to detect brain cancers.

4. Quality Education
AI can assist in personalization, allowing young girls and boys to learn more effectively.

5. Climate action
AI may be used to improve electricity demand forecasts and associated predictions from sources such as sunlight and wind.

6. Industry Innovation and Infrastructure
The industry can benefit from AI by applying it to develop reality modeling applications.

7. Gender Equality
AI can tell you how many of your applications are men and how many are women.

8. Clean Water and Sanitation
By measuring, forecasting, and modifying water efficiency, AI can ensure that more people have access to clean water.

9. Affordable and clean energy
AI can improve energy output by predicting and adapting to changing conditions and demand.

10. Sustainable cities and communities
AI can help develop electrified and even driverless vehicles, as well as smarter infrastructure planning, resulting in large and necessary reductions in air pollution.

11. Decent work and economic growth
AI can make work-life more safe, such as predictive maintenance of systems, plants, bridges.

12. Reduce Inequalities
AI can be used to identify discrepancies in legal practices and rules so that new, equal foundations can be built.

13. Responsible consumption and production
AI can accomplish more with less, reducing inefficiencies in production, improving quality, and optimizing logistics.

14. Life on land
Desertification can be noticed more easily with AI.

15. Life below water
AI can act as a lifeguard by monitoring the state of marine resources and assisting in the prevention and reduction of pollution in our oceans.

16. Partnerships for the goals
The Global Partnership on Artificial Intelligence is a multi-stakeholder project aimed at closing the gap between AI theory and reality by funding cutting-edge research and applied initiatives on AI-related objectives.

17. Peace, Justice and strong institutions
AI helps to providing equal access to justice to every one and defending everyone’s fundamental rights

Introduction to Artificial Intelligence Class 9

Social Challenges of Artificial Intelligence

“AI has the potential to assist in the solution of some of the most complex social and environmental issues, such as healthcare, disaster prediction, agriculture, environmental conservation, and cultural preservation.”

Wildlife conservation
AI-powered tools can track animal movements and analyze massive volumes of data to help us better understand where they go and what habitats we need to protect.

Disaster Awareness And Prediction
Large companies such as Google are focusing on flood prevention, using artificial intelligence to predict high-risk locations and informing the citizen.

Bullying And Hate Speech
Major social and media platforms are developing their AI bots to detect and eliminate bullying, hate speech, and other undesirable online behaviors.

Agriculture
Smart farming entails using artificial intelligence to increase overall harvest quality and accuracy. AI technology aids in the detection of plant disease, pests, and poor agricultural nutrition. AI sensors can detect and target plants, then determine the best pesticide to use in the area.

Introduction to Artificial Intelligence Class 9

Possibilities

Career Opportunities in Artificial Intelligence

1. Data Analytics
2. Natural Language Processing
3. Robotic Scientist
4. Research Scientist
5. Researcher
6. Software Engineer
7. AI Engineer
8. Data Mining and Analysis
9. Data Scientist
10. Machine Learning Engineer
11. Business Intelligence Developer
11. Big Data Engineer/ Architect
12. Business Intelligence Developer

Top Companies in Artificial Intelligence

1. Google
2. Apple
3. Amazon
4. FaceBook
5. Anki
6. DJI
7. Deepmind
8. Clarifai
9. Casetext
10. DataVisor

Skills required for Artificial Intelligence

1. There are a various numbers of skills required for AI related Jobs
2. Required Training to become a expertise in the field of Artificial Intelligence
3. Good knowledge of Math and Science related to AI
4. Required Programming Languages like Python, Java, Web related language etc.
5. Linear algebra and statistics
6. Signal processing techniques
7. Neural network architectures

Introduction to Artificial Intelligence Class 9

AI Ethics

AI ethics are a collection of principles that guide the development and use of artificial intelligence.

1. Why AI Ethics is important?

Ethical AI can help businesses run more efficiently, provide cleaner products, reduce negative environmental impacts, improve public safety, and improve human health.

2. Ethical Challenges in Artificial Intelligence

1. Cost to Innovation
2. Lack of quality data
3. Problems of Integrity
4. Lack of accuracy of data
5. Bias and discrimination
6. Reduction of human contact
7. Violation of fundamental human rights in supply chain
8. Negative impact on environment
9. Loss of human decision-making

Employability skills Class 9 Notes

• Unit 1 – Communication Skills Class 9 Notes
• Unit 2 – Self-Management Skills Class 9 Notes
• Unit 3 – Basic ICT Skills Class 9 Notes
• Unit 4 – Entrepreneurial Skills Class 9 Notes
• Unit 5 – Green Skills Class 9 Notes

Employability skills Class 9 MCQ

• Unit 1 – Communication Skills Class 9 MCQ
• Unit 2 – Self-Management Skills Class 9 MCQ
• Unit 3 – Basic ICT Skills Class 9 MCQ
• Unit 4 – Entrepreneurial Skillls Class 9 MCQ
• Unit 5 – Green Skills Class 9 MCQ

Employability skills Class 9 Questions and Answers

• Unit 1 – Communication Skills Class 9 Questionns and Answers
• Unit 2 – Self-Management Skills Class 9 Questions and Answers
• Unit 3 – Basic ICT Skills Class 9 Questions and Answers
• Unit 4 – Entrepreneurial Skills Class 9 Questions and Answers
• Unit 5 – Green Skills Class 9 Questions and Answers

Aritificial Intelligence Class 9 Notes

• Unit 1 – Introduction to Artificial Intelligence Class 9 Notes
• Unit 2 – AI Project Cycle Class 9 Notes
• Unit 3 – Neural Network Class 9 Notes
• Unit 4 – Introduction to Python Class 9 Notes
• Unit 4 : Introduction to Tools for AI Class 9 Notes
• Unit 4 : Flow of Control in Python Class 9 Notes
• Unit 4 : Introduction to Packages Python Class 9 Notes

Aritificial Intelligence Class 9 MCQ

• Unit 1 – Introduction to Artificial Intelligence Class 9 MCQ
• Unit 2 – AI Project Cycle Class 9 MCQ
• Unit 3 – Neural Network Class 9 MCQ
• Unit 4 – Introduction to Python Class 9 MCQ

Artificial Intelligence Class 9 Questions and Answers

• Unit 1 – Introduction to Artificial Intelligence Class 9 Questions and Answers
• Unit 2 – AI Project Cycle Class 9 Questions and Answers
• Unit 3 – Neural Network Class 9 Questions and Answers
• Unit 4 – Introduction to Python Class 9 Questions and Answers

Reference Textbook

The above Introduction to Artificial Intelligence Class 9 Notes was created using the NCERT Book and Study Material accessible on the CBSE ACADEMIC as a reference.

Disclaimer – 100% of the questions are taken from the CBSE textbook Introduction to Artificial Intelligence Class 9, our team has tried to collect all the correct Information from the textbook . If you found any suggestion or any error please contact us anuraganand2017@gmail.com.