CBSE Question Bank: AI Project Cycle | Artificial Intelligence for Class 10 PDF Download

 Page 1


 
CBSE Question Bank – AI – Class 10 – Chapter 3 AI Project Cycle 1 
 
 
CBSE | DEPARTMENT OF SKILL EDUCATION 
ARTIFICIAL INTELLIGENCE 
QUESTION BANK – CLASS 10 
CHAPTER 3: AI PROJECT CYCLE 
                                          One (01) Mark Questions 
 
1. Name all the stages of an AI Project cycle. 
 Problem Scoping, Data Acquisition, Data Exploration, Modeling, Evaluation 
2. What are sustainable development goals? 
 The Sustainable Development Goals (SDGs), also known as the Global Goals, were 
adopted by all United Nations Member States in 2015 as a universal call to action to 
end poverty, protect the planet and ensure that all people enjoy peace and prosperity. 
OR 
The Sustainable Development Goals (SDGs) or Global Goals are a collection of 17 
interlinked goals designed to be a "blueprint to achieve a better and more sustainable 
future for all" so that the future generations may live in peace and prosperity. 
3. Name the 4Ws of problem canvases under the problem scoping stage of the AI 
Project Cycle. 
a. Who,   b. what  c. where  d. why 
4. What is Testing Dataset? 
 The dataset provided to the model ML. algorithm after training the algorithm 
5. Mention the types of learning approaches for AI modeling. 
 Supervised, unsupervised and re-enforcement 
6. What is the objective of evaluation stage? 
 It is to evaluate whether the ML algorithm is able to predict with high accuracy or not 
before deployment. 
7. Fill in the blank:  
The analogy of an Artificial Neural Network can be made with _____________? 
(Parallel Processing) 
  
8. Which of the following is not an authentic source for data acquisition?  
a. Sensors b. Surveys  c. Web Scraping d. System Hacking 
 System Hacking 
9. Which type of graphical representation suits best for continuous type of data 
like monthly exam scores of a student? 
 Linear graph 
10. Fill in the blank: Neural Network is a mesh of multiple _____________________. 
 Hidden Layers / Layers 
Page 2


 
CBSE Question Bank – AI – Class 10 – Chapter 3 AI Project Cycle 1 
 
 
CBSE | DEPARTMENT OF SKILL EDUCATION 
ARTIFICIAL INTELLIGENCE 
QUESTION BANK – CLASS 10 
CHAPTER 3: AI PROJECT CYCLE 
                                          One (01) Mark Questions 
 
1. Name all the stages of an AI Project cycle. 
 Problem Scoping, Data Acquisition, Data Exploration, Modeling, Evaluation 
2. What are sustainable development goals? 
 The Sustainable Development Goals (SDGs), also known as the Global Goals, were 
adopted by all United Nations Member States in 2015 as a universal call to action to 
end poverty, protect the planet and ensure that all people enjoy peace and prosperity. 
OR 
The Sustainable Development Goals (SDGs) or Global Goals are a collection of 17 
interlinked goals designed to be a "blueprint to achieve a better and more sustainable 
future for all" so that the future generations may live in peace and prosperity. 
3. Name the 4Ws of problem canvases under the problem scoping stage of the AI 
Project Cycle. 
a. Who,   b. what  c. where  d. why 
4. What is Testing Dataset? 
 The dataset provided to the model ML. algorithm after training the algorithm 
5. Mention the types of learning approaches for AI modeling. 
 Supervised, unsupervised and re-enforcement 
6. What is the objective of evaluation stage? 
 It is to evaluate whether the ML algorithm is able to predict with high accuracy or not 
before deployment. 
7. Fill in the blank:  
The analogy of an Artificial Neural Network can be made with _____________? 
(Parallel Processing) 
  
8. Which of the following is not an authentic source for data acquisition?  
a. Sensors b. Surveys  c. Web Scraping d. System Hacking 
 System Hacking 
9. Which type of graphical representation suits best for continuous type of data 
like monthly exam scores of a student? 
 Linear graph 
10. Fill in the blank: Neural Network is a mesh of multiple _____________________. 
 Hidden Layers / Layers 
 
CBSE Question Bank – AI – Class 10 – Chapter 3 AI Project Cycle 2 
 
 
Two (02) Mark Questions 
 
1. What are the two different approaches for AI modelling? Define them. 
 There are two approaches for AI Modelling; Rule Based and Learning Based. 
The Rule based approach generates pre-defined outputs based on certain rules 
programmed by humans. Whereas, machine learning approach has its own rules based 
on the output and data used to train the models.  
OR 
Rule Based Approach Refers to the AI modelling where the relationship or patterns in 
data are defined by the developer. The machine follows the rules or instructions 
mentioned by the developer, and performs its task accordingly. Whereas in Learning 
based approach, the relationship or patterns in data are not defined by the developer. 
In this approach, random data is fed to the machine and it is left to the machine to 
figure out patterns and trends out of it 
2. What is a problem statement template and what is its significance? 
 The problem statement template gives a clear idea about the basic framework 
required to achieve the goal. It is the 4Ws canvas which segregates; what is the 
problem, where does it arise, who is affected, why is it a problem? It takes us straight 
to the goal. 
3. Explain any two SDGs in detail. 
 1. No Poverty: This is Goal 1 and strives to End poverty in all its forms everywhere 
globally by 2030. The goal has a total of seven targets to be achieved. 
 2. Quality Education: This is Goal 4 which aspires to ensure inclusive and equitable 
quality education and promote lifelong learning opportunities for all. It has 10 targets 
to achieve. 
 * (Any two goals can be defined) 
4. Mention the precautions to be taken while acquiring data for developing an AI 
Project. 
 It should be from an authentic source, and accurate. Look for redundant and irrelevant 
data parameters that does not take part in prediction. 
5. What do you mean by Data Features? 
 The type of data to collect,It should be relevant data. 
6. Write the names for missing stages in the given AI project cycle: 
 
 Problem scoping, Evaluation 
 
7. Draw the icons of the following SDGs: 
 
 
Gender Equality 
Clean Water and sanitation 
 
Page 3


 
CBSE Question Bank – AI – Class 10 – Chapter 3 AI Project Cycle 1 
 
 
CBSE | DEPARTMENT OF SKILL EDUCATION 
ARTIFICIAL INTELLIGENCE 
QUESTION BANK – CLASS 10 
CHAPTER 3: AI PROJECT CYCLE 
                                          One (01) Mark Questions 
 
1. Name all the stages of an AI Project cycle. 
 Problem Scoping, Data Acquisition, Data Exploration, Modeling, Evaluation 
2. What are sustainable development goals? 
 The Sustainable Development Goals (SDGs), also known as the Global Goals, were 
adopted by all United Nations Member States in 2015 as a universal call to action to 
end poverty, protect the planet and ensure that all people enjoy peace and prosperity. 
OR 
The Sustainable Development Goals (SDGs) or Global Goals are a collection of 17 
interlinked goals designed to be a "blueprint to achieve a better and more sustainable 
future for all" so that the future generations may live in peace and prosperity. 
3. Name the 4Ws of problem canvases under the problem scoping stage of the AI 
Project Cycle. 
a. Who,   b. what  c. where  d. why 
4. What is Testing Dataset? 
 The dataset provided to the model ML. algorithm after training the algorithm 
5. Mention the types of learning approaches for AI modeling. 
 Supervised, unsupervised and re-enforcement 
6. What is the objective of evaluation stage? 
 It is to evaluate whether the ML algorithm is able to predict with high accuracy or not 
before deployment. 
7. Fill in the blank:  
The analogy of an Artificial Neural Network can be made with _____________? 
(Parallel Processing) 
  
8. Which of the following is not an authentic source for data acquisition?  
a. Sensors b. Surveys  c. Web Scraping d. System Hacking 
 System Hacking 
9. Which type of graphical representation suits best for continuous type of data 
like monthly exam scores of a student? 
 Linear graph 
10. Fill in the blank: Neural Network is a mesh of multiple _____________________. 
 Hidden Layers / Layers 
 
CBSE Question Bank – AI – Class 10 – Chapter 3 AI Project Cycle 2 
 
 
Two (02) Mark Questions 
 
1. What are the two different approaches for AI modelling? Define them. 
 There are two approaches for AI Modelling; Rule Based and Learning Based. 
The Rule based approach generates pre-defined outputs based on certain rules 
programmed by humans. Whereas, machine learning approach has its own rules based 
on the output and data used to train the models.  
OR 
Rule Based Approach Refers to the AI modelling where the relationship or patterns in 
data are defined by the developer. The machine follows the rules or instructions 
mentioned by the developer, and performs its task accordingly. Whereas in Learning 
based approach, the relationship or patterns in data are not defined by the developer. 
In this approach, random data is fed to the machine and it is left to the machine to 
figure out patterns and trends out of it 
2. What is a problem statement template and what is its significance? 
 The problem statement template gives a clear idea about the basic framework 
required to achieve the goal. It is the 4Ws canvas which segregates; what is the 
problem, where does it arise, who is affected, why is it a problem? It takes us straight 
to the goal. 
3. Explain any two SDGs in detail. 
 1. No Poverty: This is Goal 1 and strives to End poverty in all its forms everywhere 
globally by 2030. The goal has a total of seven targets to be achieved. 
 2. Quality Education: This is Goal 4 which aspires to ensure inclusive and equitable 
quality education and promote lifelong learning opportunities for all. It has 10 targets 
to achieve. 
 * (Any two goals can be defined) 
4. Mention the precautions to be taken while acquiring data for developing an AI 
Project. 
 It should be from an authentic source, and accurate. Look for redundant and irrelevant 
data parameters that does not take part in prediction. 
5. What do you mean by Data Features? 
 The type of data to collect,It should be relevant data. 
6. Write the names for missing stages in the given AI project cycle: 
 
 Problem scoping, Evaluation 
 
7. Draw the icons of the following SDGs: 
 
 
Gender Equality 
Clean Water and sanitation 
 
 
CBSE Question Bank – AI – Class 10 – Chapter 3 AI Project Cycle 3 
 
 
8. Draw the graphical representation of Classification AI model. Explain in brief. 
 Classification: The classification Model works on the labelled data. For example, we 
have 3 coins of different denomination which are labelled according to their weight 
then the model would look for the labelled features for predicting the output. This 
model works on discrete dataset which means the data need not be continuous. 
OR 
In classification, data is categorized under different labels according to some 
parameters given in input and then the labels are predicted for the data. 
 
 
 
 
 
 
 
 
 
9. Draw the graphical representation of Regression AI model. Explain in brief. 
 Regression: These models work on continuous data to predict the output based on 
patterns. For example, if you wish to predict your next salary, then you would put in 
the data of your previous salary, any increments, etc., and would train the model. 
Here, the data which has been fed to the machine is continuous. 
OR 
Regression is the process of finding a model for distinguishing the data into 
continuous real values instead of using discrete values. It can also identify the 
distribution movement depending on the historical data.  
 
 
 
 
 
 
 
 
 
 
 
10. Draw the graphical representation of Clustering AI model. Explain in brief. 
 Clustering: It refers to the unsupervised learning algorithm which can cluster the 
unknown data according to the patterns or trends identified out of it. The patterns 
observed might be the ones which are known to the developer or it might even come 
up with some unique patterns out of it. 
OR 
Clustering is the task of dividing the data points into a number of groups such that 
data points in the same groups are more similar to other data points in the same 
 
 
Page 4


 
CBSE Question Bank – AI – Class 10 – Chapter 3 AI Project Cycle 1 
 
 
CBSE | DEPARTMENT OF SKILL EDUCATION 
ARTIFICIAL INTELLIGENCE 
QUESTION BANK – CLASS 10 
CHAPTER 3: AI PROJECT CYCLE 
                                          One (01) Mark Questions 
 
1. Name all the stages of an AI Project cycle. 
 Problem Scoping, Data Acquisition, Data Exploration, Modeling, Evaluation 
2. What are sustainable development goals? 
 The Sustainable Development Goals (SDGs), also known as the Global Goals, were 
adopted by all United Nations Member States in 2015 as a universal call to action to 
end poverty, protect the planet and ensure that all people enjoy peace and prosperity. 
OR 
The Sustainable Development Goals (SDGs) or Global Goals are a collection of 17 
interlinked goals designed to be a "blueprint to achieve a better and more sustainable 
future for all" so that the future generations may live in peace and prosperity. 
3. Name the 4Ws of problem canvases under the problem scoping stage of the AI 
Project Cycle. 
a. Who,   b. what  c. where  d. why 
4. What is Testing Dataset? 
 The dataset provided to the model ML. algorithm after training the algorithm 
5. Mention the types of learning approaches for AI modeling. 
 Supervised, unsupervised and re-enforcement 
6. What is the objective of evaluation stage? 
 It is to evaluate whether the ML algorithm is able to predict with high accuracy or not 
before deployment. 
7. Fill in the blank:  
The analogy of an Artificial Neural Network can be made with _____________? 
(Parallel Processing) 
  
8. Which of the following is not an authentic source for data acquisition?  
a. Sensors b. Surveys  c. Web Scraping d. System Hacking 
 System Hacking 
9. Which type of graphical representation suits best for continuous type of data 
like monthly exam scores of a student? 
 Linear graph 
10. Fill in the blank: Neural Network is a mesh of multiple _____________________. 
 Hidden Layers / Layers 
 
CBSE Question Bank – AI – Class 10 – Chapter 3 AI Project Cycle 2 
 
 
Two (02) Mark Questions 
 
1. What are the two different approaches for AI modelling? Define them. 
 There are two approaches for AI Modelling; Rule Based and Learning Based. 
The Rule based approach generates pre-defined outputs based on certain rules 
programmed by humans. Whereas, machine learning approach has its own rules based 
on the output and data used to train the models.  
OR 
Rule Based Approach Refers to the AI modelling where the relationship or patterns in 
data are defined by the developer. The machine follows the rules or instructions 
mentioned by the developer, and performs its task accordingly. Whereas in Learning 
based approach, the relationship or patterns in data are not defined by the developer. 
In this approach, random data is fed to the machine and it is left to the machine to 
figure out patterns and trends out of it 
2. What is a problem statement template and what is its significance? 
 The problem statement template gives a clear idea about the basic framework 
required to achieve the goal. It is the 4Ws canvas which segregates; what is the 
problem, where does it arise, who is affected, why is it a problem? It takes us straight 
to the goal. 
3. Explain any two SDGs in detail. 
 1. No Poverty: This is Goal 1 and strives to End poverty in all its forms everywhere 
globally by 2030. The goal has a total of seven targets to be achieved. 
 2. Quality Education: This is Goal 4 which aspires to ensure inclusive and equitable 
quality education and promote lifelong learning opportunities for all. It has 10 targets 
to achieve. 
 * (Any two goals can be defined) 
4. Mention the precautions to be taken while acquiring data for developing an AI 
Project. 
 It should be from an authentic source, and accurate. Look for redundant and irrelevant 
data parameters that does not take part in prediction. 
5. What do you mean by Data Features? 
 The type of data to collect,It should be relevant data. 
6. Write the names for missing stages in the given AI project cycle: 
 
 Problem scoping, Evaluation 
 
7. Draw the icons of the following SDGs: 
 
 
Gender Equality 
Clean Water and sanitation 
 
 
CBSE Question Bank – AI – Class 10 – Chapter 3 AI Project Cycle 3 
 
 
8. Draw the graphical representation of Classification AI model. Explain in brief. 
 Classification: The classification Model works on the labelled data. For example, we 
have 3 coins of different denomination which are labelled according to their weight 
then the model would look for the labelled features for predicting the output. This 
model works on discrete dataset which means the data need not be continuous. 
OR 
In classification, data is categorized under different labels according to some 
parameters given in input and then the labels are predicted for the data. 
 
 
 
 
 
 
 
 
 
9. Draw the graphical representation of Regression AI model. Explain in brief. 
 Regression: These models work on continuous data to predict the output based on 
patterns. For example, if you wish to predict your next salary, then you would put in 
the data of your previous salary, any increments, etc., and would train the model. 
Here, the data which has been fed to the machine is continuous. 
OR 
Regression is the process of finding a model for distinguishing the data into 
continuous real values instead of using discrete values. It can also identify the 
distribution movement depending on the historical data.  
 
 
 
 
 
 
 
 
 
 
 
10. Draw the graphical representation of Clustering AI model. Explain in brief. 
 Clustering: It refers to the unsupervised learning algorithm which can cluster the 
unknown data according to the patterns or trends identified out of it. The patterns 
observed might be the ones which are known to the developer or it might even come 
up with some unique patterns out of it. 
OR 
Clustering is the task of dividing the data points into a number of groups such that 
data points in the same groups are more similar to other data points in the same 
 
 
 
CBSE Question Bank – AI – Class 10 – Chapter 3 AI Project Cycle 4 
 
 
group and dissimilar to the data points in other groups. It is basically a collection of 
objects on the basis of similarity and dissimilarity between them. 
 
 
 
 
 
 
 
 
 
 
 
 
 
11. Explain Data Exploration stage. 
 In this stage of project cycle, we try to interpret some useful information out of the 
data we have acquired. For this purpose, we need to explore the data and try to put it 
uniformly for a better understanding.  This stage deals with validating or verification 
of the collected data and to analyze that:  
? The data is according to the specifications decided. 
? The data is free from errors. 
? The data is meeting our needs. 
 
12. What are the features of an Artificial Neural Network? 
 Any Artificial Neural Network, irrespective of the style and logic of implementation, 
has a few basic features as given below. 
? The Artificial Neural Network systems are modelled on the human brain and nervous 
system. 
? They are able to automatically extract features without feeding the input by 
programmer. 
? Every node of layer in a Neural Network is compulsorily a machine learning algorithm. 
? It is very useful to implement when solving problems for very huge datasets. 
OR 
? It can work with incomplete knowledge and may produce output even with 
incomplete information.  
? It has fault tolerance which means that corruption of one or more cells of ANN does 
not prevent it from generating output.  
? It has the ability to learn events and make decisions by commenting on similar events.  
? It has Parallel processing capability i.e. ANN have numerical strength that can perform 
more than one job at the same time.  
OR 
? Neural Networks have the ability to learn by themselves and produce the output that 
is not limited to the input provided to them. 
? The input is stored in its own networks instead of a database; hence the loss of data 
does not affect its working. 
 
Page 5


 
CBSE Question Bank – AI – Class 10 – Chapter 3 AI Project Cycle 1 
 
 
CBSE | DEPARTMENT OF SKILL EDUCATION 
ARTIFICIAL INTELLIGENCE 
QUESTION BANK – CLASS 10 
CHAPTER 3: AI PROJECT CYCLE 
                                          One (01) Mark Questions 
 
1. Name all the stages of an AI Project cycle. 
 Problem Scoping, Data Acquisition, Data Exploration, Modeling, Evaluation 
2. What are sustainable development goals? 
 The Sustainable Development Goals (SDGs), also known as the Global Goals, were 
adopted by all United Nations Member States in 2015 as a universal call to action to 
end poverty, protect the planet and ensure that all people enjoy peace and prosperity. 
OR 
The Sustainable Development Goals (SDGs) or Global Goals are a collection of 17 
interlinked goals designed to be a "blueprint to achieve a better and more sustainable 
future for all" so that the future generations may live in peace and prosperity. 
3. Name the 4Ws of problem canvases under the problem scoping stage of the AI 
Project Cycle. 
a. Who,   b. what  c. where  d. why 
4. What is Testing Dataset? 
 The dataset provided to the model ML. algorithm after training the algorithm 
5. Mention the types of learning approaches for AI modeling. 
 Supervised, unsupervised and re-enforcement 
6. What is the objective of evaluation stage? 
 It is to evaluate whether the ML algorithm is able to predict with high accuracy or not 
before deployment. 
7. Fill in the blank:  
The analogy of an Artificial Neural Network can be made with _____________? 
(Parallel Processing) 
  
8. Which of the following is not an authentic source for data acquisition?  
a. Sensors b. Surveys  c. Web Scraping d. System Hacking 
 System Hacking 
9. Which type of graphical representation suits best for continuous type of data 
like monthly exam scores of a student? 
 Linear graph 
10. Fill in the blank: Neural Network is a mesh of multiple _____________________. 
 Hidden Layers / Layers 
 
CBSE Question Bank – AI – Class 10 – Chapter 3 AI Project Cycle 2 
 
 
Two (02) Mark Questions 
 
1. What are the two different approaches for AI modelling? Define them. 
 There are two approaches for AI Modelling; Rule Based and Learning Based. 
The Rule based approach generates pre-defined outputs based on certain rules 
programmed by humans. Whereas, machine learning approach has its own rules based 
on the output and data used to train the models.  
OR 
Rule Based Approach Refers to the AI modelling where the relationship or patterns in 
data are defined by the developer. The machine follows the rules or instructions 
mentioned by the developer, and performs its task accordingly. Whereas in Learning 
based approach, the relationship or patterns in data are not defined by the developer. 
In this approach, random data is fed to the machine and it is left to the machine to 
figure out patterns and trends out of it 
2. What is a problem statement template and what is its significance? 
 The problem statement template gives a clear idea about the basic framework 
required to achieve the goal. It is the 4Ws canvas which segregates; what is the 
problem, where does it arise, who is affected, why is it a problem? It takes us straight 
to the goal. 
3. Explain any two SDGs in detail. 
 1. No Poverty: This is Goal 1 and strives to End poverty in all its forms everywhere 
globally by 2030. The goal has a total of seven targets to be achieved. 
 2. Quality Education: This is Goal 4 which aspires to ensure inclusive and equitable 
quality education and promote lifelong learning opportunities for all. It has 10 targets 
to achieve. 
 * (Any two goals can be defined) 
4. Mention the precautions to be taken while acquiring data for developing an AI 
Project. 
 It should be from an authentic source, and accurate. Look for redundant and irrelevant 
data parameters that does not take part in prediction. 
5. What do you mean by Data Features? 
 The type of data to collect,It should be relevant data. 
6. Write the names for missing stages in the given AI project cycle: 
 
 Problem scoping, Evaluation 
 
7. Draw the icons of the following SDGs: 
 
 
Gender Equality 
Clean Water and sanitation 
 
 
CBSE Question Bank – AI – Class 10 – Chapter 3 AI Project Cycle 3 
 
 
8. Draw the graphical representation of Classification AI model. Explain in brief. 
 Classification: The classification Model works on the labelled data. For example, we 
have 3 coins of different denomination which are labelled according to their weight 
then the model would look for the labelled features for predicting the output. This 
model works on discrete dataset which means the data need not be continuous. 
OR 
In classification, data is categorized under different labels according to some 
parameters given in input and then the labels are predicted for the data. 
 
 
 
 
 
 
 
 
 
9. Draw the graphical representation of Regression AI model. Explain in brief. 
 Regression: These models work on continuous data to predict the output based on 
patterns. For example, if you wish to predict your next salary, then you would put in 
the data of your previous salary, any increments, etc., and would train the model. 
Here, the data which has been fed to the machine is continuous. 
OR 
Regression is the process of finding a model for distinguishing the data into 
continuous real values instead of using discrete values. It can also identify the 
distribution movement depending on the historical data.  
 
 
 
 
 
 
 
 
 
 
 
10. Draw the graphical representation of Clustering AI model. Explain in brief. 
 Clustering: It refers to the unsupervised learning algorithm which can cluster the 
unknown data according to the patterns or trends identified out of it. The patterns 
observed might be the ones which are known to the developer or it might even come 
up with some unique patterns out of it. 
OR 
Clustering is the task of dividing the data points into a number of groups such that 
data points in the same groups are more similar to other data points in the same 
 
 
 
CBSE Question Bank – AI – Class 10 – Chapter 3 AI Project Cycle 4 
 
 
group and dissimilar to the data points in other groups. It is basically a collection of 
objects on the basis of similarity and dissimilarity between them. 
 
 
 
 
 
 
 
 
 
 
 
 
 
11. Explain Data Exploration stage. 
 In this stage of project cycle, we try to interpret some useful information out of the 
data we have acquired. For this purpose, we need to explore the data and try to put it 
uniformly for a better understanding.  This stage deals with validating or verification 
of the collected data and to analyze that:  
? The data is according to the specifications decided. 
? The data is free from errors. 
? The data is meeting our needs. 
 
12. What are the features of an Artificial Neural Network? 
 Any Artificial Neural Network, irrespective of the style and logic of implementation, 
has a few basic features as given below. 
? The Artificial Neural Network systems are modelled on the human brain and nervous 
system. 
? They are able to automatically extract features without feeding the input by 
programmer. 
? Every node of layer in a Neural Network is compulsorily a machine learning algorithm. 
? It is very useful to implement when solving problems for very huge datasets. 
OR 
? It can work with incomplete knowledge and may produce output even with 
incomplete information.  
? It has fault tolerance which means that corruption of one or more cells of ANN does 
not prevent it from generating output.  
? It has the ability to learn events and make decisions by commenting on similar events.  
? It has Parallel processing capability i.e. ANN have numerical strength that can perform 
more than one job at the same time.  
OR 
? Neural Networks have the ability to learn by themselves and produce the output that 
is not limited to the input provided to them. 
? The input is stored in its own networks instead of a database; hence the loss of data 
does not affect its working. 
 
 
CBSE Question Bank – AI – Class 10 – Chapter 3 AI Project Cycle 5 
 
 
? These networks can learn from examples and apply them when a similar event arises, 
making them able to work through real-time events. 
? Even if a neuron is not responding or a piece of information is missing, the network 
can detect the fault and still produce the output. 
? They can perform multiple tasks in parallel without affecting the system performance 
 
13. What is the purpose of getting AI Ready? 
 The world is changing with each day and we have huge data coming our way. The 
purpose of getting AI ready means taking steps to collect data around relevant 
systems, equipment, and procedures; and storing and curating that data in a way that 
makes it easily accessible to others for use in future AI applications. 
OR 
 The purpose of getting AI ready specifies the responsible and optimum use of huge 
amount of data around us to create and implement into such systems and applications 
which should make life of future generations more organized and sustainable. This 
process may lead to better lives for mankind.  
 
14. What are the different types of sources of data from where we can collect 
reliable and authentic datasets? Explain in brief. 
 Data can be a piece of information or facts and statistics collected together for 
reference or analysis. Whenever we want an AI project to be able to predict an output, 
we need to train it first using data There could be many ways and sources from where 
we can collect reliable and authentic datasets namely Surveys, Web scrapping, 
Sensors, Cameras, Observations, Research, Investigation, API etc. 
Sometimes Internet is also used to acquire data but the most important point to keep 
in mind is that the data should be taken from reliable and authentic websites only. 
Some reliable data sources are UN, Google scholar, Finance, CIA, Data.gov etc. 
 
Four (04) Mark Questions 
 
1. Explain the AI Project Cycle in detail. 
 The steps involved in AI project cycle are as given: 
? The first step is Scope the Problem by which, you set the goal for your AI project by 
stating the problem which you wish to solve with it. Under problem scoping, we look 
at various parameters which affect the problem we wish to solve so that the picture 
becomes clearer 
? Next step is to acquire data which will become the base of your project as it will help 
you in understanding what the parameters that are related to problem scoping. 
? Next, you go for data acquisition by collecting data from various reliable and authentic 
sources. Since the data you collect would be in large quantities, you can try to give it a 
visual image of different types of representations like graphs, databases, flow charts, 
maps, etc. This makes it easier for you to interpret the patterns in which your acquired 
data follows. 
? After exploring the patterns, you can decide upon the type of model you would build to 
achieve the goal. For this, you can research online and select various models which 
give a suitable output. 
? You can test the selected models and figure out which is the most efficient one. 
? The most efficient model is now the base of your AI project and you can develop your 
algorithm around it. 
? Once the modelling is complete, you now need to test your model on some newly