In this article, I am going to provide you Mock test Artificial Intelligence Class 10 Board Exam 2023. This mock test help you to score good marks in your board exam of Artificial Intelligence Class 10. Here we go!
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Mock test Artificial Intelligence Class 10 Board Exam 2023
So let us begin with MCQs. As per the latest sample paper 2023 we are going to provide you similar pattern mock test. Let’s start now!
Section [A] Objective Type Questions – Mock test Artificial Intelligence Class 10 Board Exam 2023
Q -1 Answer any 4 out of the given 6 questions on Employability Skills (1 x 4 = 4 marks)
[1] ____________ is appears to be a useful software program but once it reaches a computer it starts
behaving like a virus and destroying data.
a) WORMS
b) Adware
c) Trojan Horse
d) Ransomware
Ans.: c) Torjan Horse
[2] Darshan is working as an office assistant at Techno School. He has been appointed as Assistant Superintendent for the board exam in one of the exam centers. He has to upload some photos in the OEMS system. Which type of extension he can upload for photos?
a) .gif
b) .jpg
c) .psd
d) .pdf
Ans.: b) .jpg
[3] Manthan has set his goal to score more than 45 in the Artificial Intelligence of board exam 2023. He has ranked some activities like solving sample papers as the most important task. Which of the following step of time management he is following?
a) Organize
b) Control
c) Track
d) Prioritise
Ans.: d) Prioritise
[4] Kirtan set his goal as “He wants to become a data scientist.” So he breaks down his goal into smaller goals. Such as completing School studies with data science-related subjects and then graduation and post-graduation in the respective field. This goal refers to which of the following according to SMART method:
a) Specific
b) Measurable
c) Achievable
d) Realistic
Ans.: c) Achievable
[5] Anita has a retail shop where she sells different types of cutlery items. Where she hired two men to work with her to help her. Here she is performing which function of an entrepreneur?
a) Manage Business
b) Sharing a wealth
c) Create a new product
d) Take risks
Ans.: a) Manage business
[6] Vivek has started packers and movers services. He started with one big truck and one small truck initially. After four years of service now he has 10 big trucks and 15 small trucks for his business. Here which misconception does he overrules?
a) Every business idea needs to be unique or special
b) A person needs a lot of money to start a business
c) Both a) and b)
d) None of these
Ans.: c) Both a) and b)
Q.2. Answer any 5 out of the given 6 questions (1 x 5 = 5 marks)
[1] ____________ and ___________ are examples of voice assistants which are a major part of our digital devices.
Ans.: Apple Siri, Google Assistant, Microsoft Cortana, Amazon Alexa
[2] ___________ is a subset of Artificial Intelligence that enables machines to improve at tasks with experience (data).
a) Robotics
b) Machine Learning
c) Computer Vision
d) Natural Language Processing
Ans.: b) Machine Learning
[3] Which domain of AI has the objective of teaching machines to collect information from pixels?
a) Data Science
b) Neural Network
c) Computer Vision
d) Natural Language Processing
Ans.: c) Computer Vision
[4] Which of the following statement is not correct:
i) Data is the new gold
ii) Every company whether small or big is mining data from as many sources as possible
iii) User’s consent is not required to collect their data
a) only (i)
b) (i) and (ii)
c) (i) and (iii)
d) Only (iii)
Ans.: d) Only (iii)
[5] A large event management company has developed an AI system that recruits event hosts. It was found that the model discriminated against men. This is an example of _____________
a) AI access
b) AI Bias
c) AI Discrimination
d) Gender Discrimination
Ans.: b) AI Bias
[6] Google Translate uses Data Science to translate the data provided by users. (True/False)
Ans.: False (NLP)
Q. 3 Answer any 5 out of the given 6 questions (1 x 5 = 5 marks)
[1] Which step of the AI project cycle extracts data features?
a) Problem Scoping
b) Evaluation
c) Data Acquisition
d) Data Exploration
Ans.: d) Data Exploration
[2] Ritika is learning AI project cycle. Help her to identify which of the following is not one of the steps of the AI Project Cycle.
a) Problem Scoping
b) Develop an Algorithm
c) Data Acquisition
d) Data Exploration
Ans.: b) Develop an Algortihm
[3] A neural network has various layers. Which of the following is not a layer of a neural network?
a) Input Layer
b) Hidden Layer
c) Output Layer
d) Processing Layer
Ans.: d) Processing Layer
[4] Which of the following is working on continuous data?
a) Regression
b) Classification
c) Clustering
d) Dimensionality Reduction
Ans.: a) Regression
[5] In Natural Language Processing the words are considered as ______________ entities.
a) 1 Dimensional
b) 2 Dimensional
c) 3 Dimensional
d) N Dimensional
Ans.: d) N Dimensional
[6] Which of the following represents Quality Education SDG?
a)
b)
c)
d)
Ans.: c)
Q. 4 Answer any 5 out of the given 6 questions (1 x 5 = 5 marks)
[1] Which of the following is a common application of NLP?
a) Chatbot
b) Neural Network
c) Snapchat
d) Facelock
Ans.: a) Chatbot
[2] In NLP, ___________ is a term used for any word or number or special character occurring in a sentence.
a) Document Vector
b) Corpus
c) Token
d) Stemming
Ans.: c) Token
[3] State True or False – In the sentence segmentation the whole text is divided into phrases.
Ans.: False
[4] Which of the following is a stopword?
a) the
b) art
c) word
d) token
Ans.: a) the
[5] Identify the step of text normalization:
a) Converting to common case
b) Tokenisation
c) Lemmatization
d) Stemming
Ans.: d) Stemming
[6] Which of the following returns the occurrences of each word and construct the vocabulary for the corpus?
a) Bag of words
b) Tokenisation
c) Stemming
d) Lemmatization
Ans.: a) Bag of words
Q. 5 Answer any 5 out of the given 6 questions (1 x 5 = 5 marks)
[1] State True or False – “Precision provides a measure of how accurately the model is able to identify the data”
Ans.: False (Recall)
[2] Trisha is working on an AI model. She has compared both reality and prediction. Which tool she has used to do the comparison?
a) Problem Statement
b) Chatbot
c) ChatGPT
d) Confusion Matrix
Ans.:d) Confusion Matrix
[3] Identify the formula component required to compute the accuracy.
a) Only True Positive Cases and Total Cases
b) True Positive, True Negative, and Total Cases
c) True Negative, False Negative Only
d) Fale Positive and False Negative
Ans.: b) True Positive, True Negative and Total Cases
[4] ____________ is the result of a balance between precision and recall.
a) Accuracy
b) Classification
c) F1 Score
d) Confusion Matrix
Ans.: c) F1 Score
[5] Which of the following is not correct about the F1 score:
a) When Precision and Recall both are low, F1 Score is low
b) When Precision is low but Recall is high, the F1 score is high
c) When Precision and Recall both are high, the F1 score is high
d) When Precision is High but recall is low, the F1 score is low
Ans.: b) When Precision is low but Recall is highm the F1 Score is high
[6] Sunil is confused with the terms used in the evaluation stage. Suggest her the term can be defined as the percentage of true positive cases versus all the cases where the prediction is true.
a) Accuracy
b) Precision
c) Recall
d) F1 Score
Ans.: b) Precision
Section [B] Subjective Type Questions
Answer any 3 out of the given 5 questions on Employability Skills (2 x 3 = 6 marks)
Answer each question in 20 – 30 words.
Q – 6 How do physical exercise and yoga help in stress management?
Ans.:
Physical Exercise
When stress affects the brain, rest of the body also feels the impact. Physical exercise in the form of walking, skipping or for that matter indulging in any sports has been found to relieve stress as they stabilize mood, improve self-esteem and induce sleep.
Yoga
Yoga is a school of Hindu philosophy that reduces stress. Yoga includes a series of postures and breathing exercises practiced to achieve control of body and mind.
Q – 7 “Amir Hussain” the captain of the Jammu and Kashmir para cricket team, An accident at a sawmill left an eight-year-old Amir Hussain Lone without his arms. For three years after, he struggled in a hospital as he recovered. However, from the time when people suggested to his father that he “get rid of him”, Amir not only managed to make his feet double as his hands but even learned to swim and play cricket. Amir has become a pride for his family. By this story write the what qualities a self-motivated person has.
Ans.: A person like Amir Hussain is a self motivated person. The self motivated person has following qualitites:
1. Know what they want from life
2. Are Focused
3. Know what is important
4. Are dedicated to fulfill their dreams
Q – 8 Write the similarities between the computer file system and the physical file system we are managing in the school.
Ans.: In any school (or office), each teacher has a separate cabinet where they keep the files of different students or classes on separate shelves.
Similarly, information on a computer is stored in electronic files, which can be put into separate folders. It is easier to manage the electronic files as they can be simply copied, moved, renamed or even deleted.
Q – 9 Identify the functions performed by the entrepreneur from the given statements:
i) Henil makes juice and sells it to the local shopkeepers in bulk. He decides to purchase the fruits from farmers directly.
ii) Navin has a computer repair shop. He was providing excellent services in his area. Now he thought to expand his network to the various branches. So he started investing, hiring new employees, and working with vendors.
iii) Smita has her beauty parlor near her residence. She has a staff of 7 other females for her beauty parlor. She framed a few rules for all for setting performance standards and taking corrective actions.
iv) Rashmi is selling a product and is involved in the promotion, advertising, distribution, and customer services, making people aware of offerings and making sales.
Ans.:
i) Taking Decision, managing business
ii) Risk Taking
iii) Controlling
iv) marketing
Q – 10 A person who chooses a career as an entrepreneur goes through a career process. Explain any two steps of the career process of an entrepreneur.
Ans.: A person who chooses a career as an etnrepreneur goes thorugh a career process goes through these three steps:
1. Enter
2. Survive
3. Grow
1. Enter – When an entrepreneur is starting, they are just entering the market to do business. Example – Sameer is starting cold drink shop in his local area.
2. Survive – There are many entrepreneurs in the market. The entrepreneur has to remain in a competitive market. There are many cold drink shops and ice cream parlors in the area but Sameer survies in the competition and does well.
3. Grow – Once the business is stable, an entrepreneur thinks about expanding his or her business. Example – After 3 years Sameer is thinking to produces fruit juice in the local area.
Answer any 4 out of the given 6 questions in 20 – 30 words each (2 x 4 = 8 marks)
Q – 11 How do automatic cars and face locks use Computer Vision? Explain in detail.
Ans.:
In Automatic Cars, Computer Vision scans live objects and anlyse them and based on this car decides to keep running or stop.
In facelocks owner can set up his face to unlock the device. The front camera detects the face then capture it, and save its features during initiation. Next time onwards when face matched to the image save in phone it will be unlocked.
Q – 12 Differentiate between regression and classification.
| Regression | Classification |
| It works on continuous or real data. | It works on discrete data. |
| For example in the grading system, students are classified according to the grades they score marks in the exam. | For example, if next month’s salary is to be predicted then the previous salary, any increments, etc required. |
| It attempts to find the best-fit line and predicts the accurate output. | It tries to find the decision boundary which divides the dataset into different classes. |
| It can solve the problems such as house price predictions, weather predictions, etc. | It can be useful in identifying spam emails, spotting cancer cells and speech recognition. |
| It can be further divided into two categories: Linear and Non-linear regression | It can be divided into Binary Classifiers and Multiclass classifiers |
Q – 13 Explain tokenization in short with an example.
Ans.: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.
Example:
Tokenization is used in natural language processing to split paragraphs and sentences into smaller units that can be more easily assigned meaning
As this sentence contains 22 words, hence it is said that it has 22 tokens.
Q – 14 What do you mean by automatics summarization?
Ans.:
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.
Q – 15] Define :
i) Kinesthetic Intelligence
ii) Intrapersonal Intelligence
Ans.:
i) Kinesthetic Intelligence: It refers to the capacity to manipulate objects and use a variety of physical skills. This intelligence also involves a sense of timing and the perfection of skills through mind–body union. Athletes, dancers, surgeons, and crafts people exhibit well-developed bodily kinesthetic intelligence.
ii) Intrapersonal Intelligence: Intrapersonal intelligence is the capacity to understand oneself and one’s thoughts and feelings, and to use such knowledge in planning and directioning one’s life. Intra-personal intelligence involves not only an appreciation of the self, but also of the human condition. It is evident in psychologist, spiritual leaders, and philosophers. These young adults may be shy. They are very aware of their own feelings and are self-motivated.
Q – 16 A route prediction model has predicted a short route and in reality, it is a short route. Explain this condition according to the confusion matrix component.
Ans.: When the predition and reality matches in evaluation, it is to be said as True Positive condition. True postive cases is used to compute precision, recall, and accuracy.
Answer any 3 out of the given 5 questions in 50– 80 words each (4 x 3 = 12 marks)
Q – 17 Write any four applications of AI. Explain each of them
Ans.:
1. Search Engine (Google) – Every now and then, we surf the internet for things on Google without realizing how efficiently Google always responds to us with accurate answers. Not only does it come up with results to our search in a matter of seconds, it also suggests and auto-corrects our typed sentences.
2. Virtual Assistants: We nowadays have pocket assistants that can do a lot of tasks at just one command. Alexa, Google Assistant, Cortana, Siri are some very common examples of the voice assistants which are a major part of our digital devices.
3. Navigatio Apps: To help us navigate to places, apps like UBER and Google Maps come in haman. Thus, one no longer needs to stop repeatedly to ask for directions.
4. AI has completely enhanced the gaming experience for its users. A lot of games nowadays are backed up with AI which helps in enhancing the graphics, come up with new difficulty levels, encourage gamers, etc.
Q – 18 What are Artificial Intelligence, Machine Learning, and Deep Learning? How they are associated with each other?
Ans.:
Artificial Intelligence: A machine having ability to mimic humans, make decisions by learning from data, predicts the future and improve by its own is called Artificial Intelligence.
Machine Learning: It is a subset of Artificial Inelligence that is capable to teach itself based on algorithms and the machine becomes smarter over time without human intervention.
Deep Learning: It is a subset of Artificial Intelligence which inspired the way the human brain filters information. It works on input layers to predict and classify information.
Deep Learning and Machine learning are subset of AI that solves complex problems. In machine learning, machines becomes intelligent and develops their own algorithms. Deep learning is more advanced form of AI.
Q – 19 Palak is working as a coordinator in a school. Her principal gave her the task to create a timetable for the upcoming academic year. Answer the following questions where she is confused.
- Write the problem statement template for her.
- List out the ways how she can collect data.
Ans.: 1.
| Our | Teachers | Who? |
| have problem that | computerised timetable | What? |
| while | A manual timetable takes too much time to prepare and is not accurate | Where? |
| An ideal solution would | To provide a accurate timetable in few clicks | Why? |
2. She can collect data using google forms or surveys, general discussions with colleagues, and observations of the previous year time table.
Q – 20 Rajni has been given the task to create a dictionary and create a document vector. Help him to complete the task. The documents are given below:
Document 1: Mona wants to be an entrepreneur.
Document 2: entrepreneur doing business.
Document 3: she knows an entrepreneur.
Ans.:
1) Create a Dictionary
| Mona | wants | to | be | an | entrepreneur |
| doing | business | ||||
| she | knows |
2) Create a document vector
| Mona | wants | to | be | an | entrepreneur | doing | business | she | knows |
| 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 |
| 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 |
| 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 1 |
Q – 21 Consider the given confusion matrix and calculate accuracy, precision, recall, and F1 score.
| True | False | |
| True | 120 | 80 |
| False | 55 | 27 |
Ans.:
True Positives: 120
True Negatives:27
False Positives: 80
False Negatives: 55
Accuracy = ((TP+TN)/(TP+TN+FP+FN))*100%= ((120+27)/(120+27+80+55))*100=(147/282)*100%=0.52
Precision=(TP/(TP+FP))*100%=(120/(120+80))*100%=0.60
Recall=(TP/(TP+FN))*100%=(120/(120+55))*100%=0.69
F1 Score=2*((Precision*Recall)/(Precision+Recall))=2*((0.60*0.69)/(0.69+0.60))=2*((0.414/1.29))=2*0.32=0.64
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