CBSE Artificial Intelligence Class 10 Sample Paper – A Comprehensive Guide

Ans.: Self Motivation
Reference: Employability Skills NCERT, Unit 2 Self Management Skills Page no: 52

Ans.: (c) Hover –

Drag and Drop: To move an item, you need to click it, and then holding the mouse button down, move the item to a new location. After you move the item to the new location, you release the mouse button. This is called drag and drop.

Double Click:Double-clicking means to quickly click theleft mous e button twice. When we double click on a file, it will open the file.

Single click : When you click a particular file, it gets selected
Reference: Employability Skills NCERT, Unit 3 ICT Skills , Page No.: 67

Ans.: (a) Both A and R are correct and R is the correct explanation of A
Reference: Employability Skills NCERT, Unit 4 Entreprenerial Skills , Page No.: 100

Ans.: d) Tracking

Organising – Planning our day to day activities, making time table to do work, Keeping our surroounding clean, putting things back where they belong is called organising.

Prioritising – Making a to-do list that has all our activities and we rank them in the order of importance.

Controlling – Controlling the time and activites
Reference: Employability Skills NCERT, Unit 2 Self Management Skills Page no: 60

Ans.: (d) Linguistic barrier

Interpesonal barrier – Barriers to interpersonal communication occur when the sender’s message is received differently from how it was intended. It is also very difficult to communicate with someone who is not willing to talk or express their feelings and views. Stage fear, lack of will to communicate, personal differences can create interpersonal barriers to communication.

Physical barrier – is the environmental and natural condition that act as a barrier in communication in
sending message from sender to receiver. Not being able to see gestures, posture and general body language
can make communication less effective. For example, text messages are often less effective than face-to-face communication.

Organisational barrier – Organisations are designed on the basis of formal hierarchical structures that follow performance standards, rules and regulations, procedures, policies, behavioural norms, etc. All these affect the free flow of communication in organisations and therefore, need to be suitably managed. Superior-subordinate relationships in a formal organisational structure can be a barrier to free flow of communication. Also, sometimes due to the stringent rules, the employees find it difficult to communicate with their peers too.

Reference: Employability Skills NCERT, Unit 1 Communication Skills Page no: 21

Ans.: (c) Affordable and clean energy

Protect Life on Land: Cutting of trees is leading to soil erosion and making land dry and unusable for cultivation. Planting more tree to replace the ones that we have cut is an important step towards sustainable development.

Clean water and sanitation: We must make efforts to make India free of open defecation by building toilets and creating awareness towards sanitation. Industrial pollution is polluting our water resources, which in near future will cause scarcity of clean drinking and usable water. We must take measurable steps by promoting awareness to keep water sources clean.

Reduce inequalities
To reduce inequalities we can
1. be helpful to one another.
2. be friendly with everyone.
3. include everyone while working or playing.
4. help others by including everyone whether they are small or big, girl or boy, belong to any class or caste.
Reference: Employability Skills NCERT, Unit 5 Green Skills Page no: 111

Ans.: (b) Data Privacy

AI Ethics – We need to keep aspects relating to ethical practices in mind while developing solutions using AI. Every person has a different perspective and hence he/she takes decisions according to their moralities.

AI Bais: Everyone has a bias of their own no matter how much one tries to be unbiased, we in some way or the other have our own biases even towards smaller things. Biases are not negative all the time. Sometimes, it is required to have a bias to control a situation and keep things working.

AI Access: The people who can afford AI enabled devices make the most of it while others who cannot are left behind. Because of this, a gap has emerged between these two classes of people and it gets widened with the rapid advancement of technology.
Reference: CBSE Facilitator Handbook Class 10 – Chapter 2 – Introduction to AI : Foundational Concetps , Page no.: 24

Ans.: (c) Statement1 is correct but Statement2 is incorrect

Statement 1 : There are three layers in a neural network.
Statement 2: The first layer of the neural network is known as input layer.
Reference: CBSE Facilitator Handbook Class 10 – Chapter 2 – Introduction to AI: Basics of AI, Page no.: 40

Ans.: Larger

As seen in the figure given, the larger Neural Networks tend to perform better with larger amounts of data whereas the traditional machine learning algorithms stop improving after a certain saturation point.

Reference: CBSE Facilitator Handbook Class 10 – Chapter 2 – Introduction to AI: Basics of AI, Page no.: 40

Ans.: (c) csv

As seen in the figure given, the larger Neural Networks tend to perform better with larger amounts of data whereas the traditional machine learning algorithms stop improving after a certain saturation point.

Reference: CBSE Facilitator Handbook Class 10 – Chapter 4 – Data Sciences, Page no.: 63

Ans.: (b) Rare word

Stop Word – if the words have highest occurrence in all the documents of the corpus, they are said to have negligible value hence they are termed as stop words.

Rare Word – The words occurs least but add the most value to the corpus is known as Rare word.

Frequent Word – The words which have adequate occurrence in the corpus are said to have some amount of value and are termed as frequent words.

Removable Word – The stop words can be termed as removable words because they are mostly removed at pre-processing.

Reference: CBSE Facilitator Handbook Class 10 – Chapter 6 – Natural Language Processing, Page no.: 115

Ans.: (c) iii and iv
1. and 2. uses AI technology as they are trained by the given data and learn from their behaviour

3. and 4 uses sensors but not learn from the data

Reference: CBSE Facilitator Handbook Class 10 – Chapter 1 – Introduction to AI: Foundational Concepts of AI, Page no.: 16

Ans.: Data Features/Data

Reference: CBSE Facilitator Handbook Class 10 – Chapter 2 – AI Project Cycle, Page no.: 35

Ans.: (b) Target Advertisements
If you thought Search would have been the biggest of all data science applications, here is a challenger – the entire digital marketing spectrum. Starting from the display bails on various websites to the digital billboards at the airports – almost all of them are decided by using data science algorithms. This is the reason why digital ads have been able to get a much higher CTR (Call-Through Rate) than traditional advertisements. They can be targeted based on a user’s past behaviour.

Text Summarization – Application of NLP

Face lock in smartphones – Application of CV

Email Filters – Application of NLP
Reference: CBSE Facilitator Handbook Class 10 – Chapter 4 – Data Science, Page no.: 56

Ans.: (b) Object Dtection

Instance Segmentation is the process of detecting instances of the objects, giving them a category and then giving each pixel a label based on that. A segmentation algorithm takes an image as input and outputs a collection of regions (or segments).

Classification – Image Classification problem is the task of assigning an input image one label from a fixed set of categories. This is one of the core problems in CV that, despite its simplicity, has a large variety of practical applications.

Image Segmentation – There is no such terms in Computer Vision
Reference: CBSE Facilitator Handbook Class 10 – Chapter 5 – Computer Vision, Page no.: 78

Ans.: Smart Bot

Reference: CBSE Facilitator Handbook Class 10 – Chapter 6 – Natural Language Processing, Page no.: 105

Ans.: (b) Precision and Recall

Reference: CBSE Facilitator Handbook Class 10 – Chapter 7 – Evaluation, Page no.: 127

Ans.: Deep Learning

It enables software to train itself to perform tasks with vast amounts of data. In Deep Learning, the machine is trained with huge amounts of data which helps it in training itself around the data. Such machines are intelligent enough to develop algorithms for themselves. Deep Learning is the most advanced form of Artificial Intelligence out of these three. Then comes Machine Learning which is intermediately intelligent and Artificial Intelligence covers all the concepts and algorithms which, in some way or the other mimic human intelligence.

Reference: CBSE Facilitator Handbook Class 10 – Chapter 1 – Introduction to AI: AI Foundational Concetps, Page no.: 1

Ans.: (b) Both Statement1 and Statement2 are incorrect

The output given by the AI model is known as prediction.
The real scenario is known as Prediction.

Reference: CBSE Facilitator Handbook Class 10 – Chapter 7 – Evaluation, Page no.: 119

Ans.: (a) Data gathered with respect to stadium, bowlers, opponent team and health is known as Testing Data.

Reference: CBSE Facilitator Handbook Class 10 – Chapter 4 – Data Science, Page no.: 60

Ans.: Three Channels – RGB

Reference: CBSE Facilitator Handbook Class 10 – Chapter 5 – Computer Vision, Page no.: 83

Ans.: b) Sentiment Analysis

The goal of sentiment analysis is to identify sentiment among several posts or even in the same post where emotion is not always explicitly expressed. Companies use Natural Language Processing applications, such as sentiment analysis, to identify opinions and sentiment online to help them understand what customers think about their products and services (i.e., “I love the new iPhone” and, a few lines later “But sometimes it doesn’t work well” where the person is still talking about the iPhone) and overall indicators of their reputation. Beyond determining simple polarity, sentiment analysis understands sentiment in context to help better understand what’s behind an expressed opinion, which can be extremely relevant in understanding and driving purchasing decisions.

Virtual Assistants –
Nowadays Google Assistant, Cortana, Siri, Alexa, etc have become an integral part of our lives. Not only can we talk to them but they also have the abilities to make our lives easier. By accessing our data, they can help us in keeping notes of our tasks, make calls for us, send messages and a lot more. With the help of speech recognition, these assistants can not only detect our speech but can also make sense out of it. According to recent researches, a lot more advancements are expected in this field in the near future.

Text classification –
Text classification makes it possible to assign predefined categories to a document and organize it to help you find the information you need or simp lify some activities. For example, an application of text categorization is spam filtering in email.

Automatic Summarization –
Information overload is a real problem when we need to access a specific, important piece of information from a huge knowledge base. Automatic summarization is relevant not only for summarizing the meaning of documents and information, but also to understand the emotional meanings within the information, such as in collecting data from social media. Automatic summarization is especially relevant when used to provide an overview of a news item or blog post, while avoiding redundancy from multiple sources and maximizing the diversity of content obtained.

Reference: CBSE Facilitator Handbook Class 10 – Chapter 6 – Natural Language Processing, Page no.: 100

Ans.: Overfitting

Reference: CBSE Facilitator Handbook Class 10 – Chapter 5 – Computer Vision, Page no.: 119

Ans.: (c) Natural Language Processing

Reference: CBSE Facilitator Handbook Class 10 – Chapter 1 – Introduction to AI – AI Foundational Concepts , Page no.: 22

Ans.: Accuracy

Reference: CBSE Facilitator Handbook Class 10 – Chapter7 – Evaluation , Page no.: 123

Ans.: (c) Pixel

Reference: CBSE Facilitator Handbook Class 10 – Chapter 5 – Computer Vision , Page no.: 79

Ans.: (b) Grammatical structure of a sentence
Syntax refers to the grammatical structure of a sentence. When the structure is present, we can start interpreting the message. Now we also want to have the computer do this. One way to do this is to use the part-of-speech tagging. This allows the computer to identify the different parts of a speech.

Reference: CBSE Facilitator Handbook Class 10 – Chapter 6 – Natural Language Processing , Page no.: 106

Ans.: (c) Bag of words
Bag of Words is a Natural Language Processing model which helps in extracting features out of the text which can be helpful in machine learning algorithms. In bag of words, we get the occurrences of each word and construct the vocabulary for the corpus.

Sentence Segmentation –
Under sentence segmentation, the whole corpus is divided into sentences. Each sentence is taken as a different data so now the whole corpus gets reduced to sentences.

Tokenisation –
After segmenting the sentences, each sentence is then further divided into tokens. Tokens is a term used for any word or number or special character occurring in a sentence. Under tokenisation, every word, number and special character is considered separately and each of them is now a separate token.

Text Normalisation –
In Text Normalisation, we undergo several steps to normalise the text to a lower level. Before we begin, we need to understand that in this section, we will be working on a collection of written text. That is, we will be working on text from multiple documents and the term used for the whole textual data from all the documents altogether is known as corpus. Not only would we go through all the steps of Text Normalisation, we would also work them out on a corpus.

Reference: CBSE Facilitator Handbook Class 10 – Chapter 6 – Natural Language Processing , Page no.: 112

Ans.: (d) Spam Filter

Rest of all conditions result in a high false positivve cost.

Reference: CBSE Facilitator Handbook Class 10 – Chapter 7 – Evaluation , Page no.: 126

Ans.:
1. Use simple language
2. Be respectful of others opinions
3. Do not form assumptions on culture, religion or geography
4. Try to communicate in person as much as possible
5. Use visuals
6. Take help of a translator to overcome differences in language
(2 marks for any two correct points from the above)

Reference: CBSE Employability skills – Chapter 1 – Communication Skills , Page no.: 22

Ans.:
1. The process of goal setting in your life helps you decide on how to live your life, where you want to be, and how you want to be in the future.
2. It helps you to focus on the end result instead of less important work.
3. This will make you successful in your career and personal life.
(2 marks for any one valid justification given above or any relevant answer)

Reference: CBSE Employablity Skills – Chapter 2 – Self Management Skills , Page no.: 55

Ans.:
A Trojan Horse is a type of malware which disguises itself i.e., it appears to be a useful software program but once it reaches a computer it starts behaving like a virus and destroys data.

(1 mark for acting like useful program and, 1 mark for the words destroying/corrupting/deleting data)
or
(only ½ marks will be allotted if only malware/harmful program/virus/ term is mentioned)

Reference: CBSE Employablity Skills – Chapter 3 – Basic ICT Skills , Page no.: 81

Ans.:
Society is helping entrepreneurs by
1. Creating needs
2. Providing raw material
3. buying/selling of items
4. making money
(1 mark for acting like useful program and, 1 mark for the words destroying/corrupting/deleting data)
or
(only ½ marks will be allotted if only malware/harmful program/virus/ term is mentioned)

Reference: CBSE Employablity Skills – Chapter 4 – Entrepreneurial Skills , Page no.: 85

Ans.:
1. Use of fertilisers, pesticides,etc for increasing the production of crops.
2. Cutting down of forests for personal use such as construction of buildings, factories etc
(1 mark for each valid point, or any two relevant answers other than the above)

Reference: CBSE Employablity Skills – Chapter 5 – Green Skills , Page no.: 103

Ans.:
1. To provide customized notifications and recommendations.
2. To improve the efficiency and accuracy of the app.
(2 marks for any one correct point with explanation)

Reference: CBSE AI Facilitator Handbook Class 10 – Chapter 1 Inorduction to AI: AI foundational concepts -, Page no.: 25,26

Ans.:
Clustering model/Unsupervised learning is used to organize the unlabeled input data into groups based on features.
Clustering is an unsupervised learning algorithm which can cluster 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.
(1 mark for identifying the name of the algorithm and 1 mark for explanation)

Reference: CBSE AI Facilitator Handbook Class 10 – Chapter 2 AI Project Cycle-, Page no.: 39

Ans.:
While accessing data from any of the data sources, following points should be kept in mind:
1. Data which is available for public usage only should be taken up.
2. Personal datasets should only be used with the consent of the owner.
3. One should never breach someone’s privacy to collect data.
4. Data should only be taken from reliable sources as the data collected from random sources can be wrong or unusable.
5. Reliable sources of data ensure the authenticity of data which helps in the proper training of the AI model.
6. Data should be relevant to the problem.
(any two; 1 mark for each valid point)
Reference: CBSE AI Facilitator Handbook Class 10 – Chapter 4 Data Science -, Page no.: 63

Ans.:
Resolution of an image refers to the number of pixels in an image, across the width and height.
For example a monitor resolution of 1280×1024. This means there are 1280 pixels from one side to the other, and 1024 from top to bottom.
(1 mark for explanation; 1 mark for example)

Reference: CBSE AI Facilitator Handbook Class 10 – Chapter 5 Computer Vision-, Page no.: 80

Ans.:
Stopwords in the given sentence which should not be removed are:
@, . (fullstop) ,_(underscore) , 123(numbers)
These tokens are generally considered as stopwords, but in the above sentence, these tokens are part of email id. removing these tokens may lead to invalid website address and email ID. So these words should not be removed from the above sentence.
(1 mark for identifying any two stop words from the above, and 1 mark for the valid justification.)

Reference: CBSE AI Facilitator Handbook Class 10 – Chapter 6 Natural Language Processing-, Page no.: 110

Ans.:
When a machine possesses the ability to mimic human traits, i.e., make decisions, predict the future, learn and improve on its own, it is said to have artificial intelligence. In other words, you can say that a machine is artificially intelligent when it can accomplish tasks by itself – collect data, understand it, analyse it, learn from it, and improve it.
Machines become intelligent once they are trained with some data which helps them achieve their tasks. AI machines also keep updating their knowledge to optimise their output. For example, Netflix gives us recommendations on the basis of what we like. Whenever we start liking a new genre, it updates and gives better suggestions.
(2 marks for definition of Artificial intelligence which includes any of the highlighted terms,
2 mark for an example explanation of how machines become intelligent or only 1 mark for any AI machine example which mimic human traits without explanation))

Reference: CBSE AI Facilitator Handbook Class 10 – Chapter 1 Introduction to AI-, Page no.: 14, 15

Ans.: The learning based approaches shown in the given figures are Supervised learning and Unsupervised learning.

Figure 1: In a supervised learning model, the dataset which is fed to the machine is labelled. In other words, we can say that the dataset is known to the person who is training the machine only then he/she is able to label the data. A label is some information which can be used as a tag for data.

Here, labelled images of dog and cat are fed into the model and trained. The model correctly identifies the given input as dog.

Figure 2: An unsupervised learning model works on unlabelled dataset. This means that the data which is fed to the machine is random and there is a possibility that the person who is training the model does not have any information regarding it. The unsupervised learning models are used to identify relationships, patterns and trends out of the data which is fed into it. It helps the user in understanding what the data is about and what are the major features identified by the machine in it.

Here, images of a set of animals are fed into the AI model and the model clusters them based on similar features

(1 mark each for identifying each term supervised learning and unsupervised learning; 1 mark per explanation of each term)

Reference: CBSE AI Facilitator Handbook Class 10 – Chapter 2 AI Project Cycle-, Page no.: 37,38

Ans.:
Yes, we might face any challenges if we try to teach computers how to understand and interact in human languages.
The possible difficulties are:
1.
Arrangement of the words and meaning – the computer has to identify the different parts of a speech. Also, it may be extremely difficult for a computer to understand the meaning behind the language we use.
2.
Multiple Meanings of a word – same word can be used in a number of different ways which according to the context of the statement changes its meaning completely.
3.
Perfect Syntax, no Meaning – Sometimes, a statement can have a perfectly correct syntax but it does not mean anything. For example, take a look at this statement:
Chickens feed extravagantly while the moon drinks tea.
This statement is correct grammatically but does this make any sense? In Human language, a perfect balance of syntax and semantics is important for better understanding.

(1 mark for Yes and 1 mark each for the points on possible difficulties)

Reference: CBSE AI Facilitator Handbook Class 10 – Chapter 6 NLP-, Page no.: 106,107