Artificial Intelligence Class 10

Teachers and Examiners (CBSESkillEduction) collaborated to create the Evaluation Class 10 Questions and Answers. All the important QA are taken from the NCERT Textbook Artificial Intelligence ( 417 ) class X.

Evaluation Class 10 Questions and Answers

1. What is evaluation?
Answer – By feeding test datasets into AI models and comparing the outputs to real-world results, evaluation is the process of determining the dependability of any AI model is known as evaluation. Various evaluation methods may be used, depending on the kind and function of the model. Keep in mind that it is not advised to utilize the model’s construction data for its evaluation.

Evaluation Class 10 Questions and Answers

2. What is overfitting?
Answer – Overfitting happens when a statistical model matches its training data exactly. When this occurs, the algorithm’s goal is lost because it is unable to accurately execute against unseen data.

3. What is Confusion Matrix?
Answer – The result of comparison between the prediction and reality can be recorded in what we call the confusion matrix. The confusion matrix allows us to understand the prediction results. Note that it is not an evaluation metric but a record which can help in evaluation.

Evaluation Class 10 Questions and Answers

4. What is the purpose of Accuracy in AI and give the example of equation?
Answer – The percentage of accurate predictions among all the observations is what is meant by the term accuracy. A prediction is deemed accurate if it agrees with reality. There are two circumstances in this case where the Prediction and Reality match: True Positive and True Negative. The equation for accuracy is –

5. What is Precision and give the example of equation?
Answer – Precision is defined as the percentage of true positive cases versus all the cases where the prediction is true. That is, it takes into account the True Positives and False Positives.
Evaluation Class 10 Questions and Answers

6. What is Recall in AI and give the example of equation?
Answer – The percentage of pertinent documents that are successfully retrieved is known as recall. Recall, for instance, is the ratio of the number of accurate results to the number of results that should have been returned for a text search on a set of documents.

7. What is F1 Score and give the example of equation?
Answer – F1 score can be defined as the measure of balance between precision and recall. By calculating the harmonic mean of a classifier’s precision and recall, the F1-score integrates both into a single metric. It mainly used to compare the effectiveness of two classifiers.

Employability skills Class 10 Notes

• Unit 1- Communication Skills Class 10 Notes
• Unit 2- Self-Management Skills Class 10 Notes
• Unit 3- Basic ICT Skills Class 10 Notes
• Unit 4- Entrepreneurial Skills Class 10 Notes
• Unit 5- Green Skills Class 10 Notes

Employability skills Class 10 MCQ

• Unit 1- Communication Skills Class 10 MCQ
• Unit 2- Self-Management Skills Class 10 MCQ
• Unit 3- Basic ICT Skills Class 10 MCQ
• Unit 4- Entrepreneurial Skills Class 10 MCQ
• Unit 5- Green Skills Class 10 MCQ

Employability skills Class 10 Questions and Answers

• Unit 1- Communication Skills Class 10 Questions and Answers
• Unit 2- Self-Management Skills Class 10 Questions and Answers
• Unit 3- Basic ICT Skills Class 10 Questions and Answers
• Unit 4- Entrepreneurial Skills Class 10 Questions and Answers
• Unit 5- Green Skills Class 10 Questions and Answers

Artificial Intelligence Class 10 Notes

• Unit 1 – Introduction to Artificial Intelligence Class 10 Notes
• Unit 2 – AI Project Cycle Class 10 Notes
• Unit 3 – Natural Language Processing Class 10 Notes
• Unit 4 – Evaluation Class 10 Notes
• Advanced Python Class 10 Notes
• Computer Vision Class 10 Notes

Artificial Intelligence Class 10 MCQ

• Unit 1 – Introduction to Artificial Intelligence Class 10 MCQ
• Unit 2 – AI Project Cycle Class 10 MCQ
• Unit 3 – Natural Language Processing Class 10 MCQ
• Unit 4 – Evaluation Class 10 MCQ

Artificial Intelligence Class 10 Questions and Answers

• Unit 1 – Introduction to Artificial Intelligence Class 10 Questions and Answers
• Unit 2 – AI Project Cycle Class 10 Questions and Answers
• Unit 3 – Natural Language Processing Class 10 Questions and Answers
• Unit 4 – Evaluation Class 10 Questions and Answers

Teachers and Examiners (CBSESkillEduction) collaborated to create the Natural Language Processing Class 10 Questions and Answers. All the important MCQs are taken from the NCERT Textbook Artificial Intelligence ( 417 ) class X.

Natural Language Processing Class 10 Questions and Answers

1. What do you mean by Natural Language Processing?
Answer – The area of artificial intelligence known as natural language processing, or NLP, is dedicated to making it possible for computers to comprehend and process human languages. The interaction between computers and human (natural) languages is the focus of artificial intelligence (AI), a subfield of linguistics, computer science, information engineering, and artificial intelligence. This includes learning how to programme computers to process and analyze large amounts of natural language data.

2. What are the different applications of NLP which are used in real-life scenario?
Answer – Some of the applications which is used in the real-life scenario are –
a. Automatic Summarization – Automatic summarization is useful for gathering data from social media and other online sources, as well as for summarizing the meaning of documents and other written materials. When utilized to give a summary of a news story or blog post while eliminating redundancy from different sources and enhancing the diversity of content acquired, automatic summarizing is particularly pertinent.

b. Sentiment Analysis – In posts when emotion is not always directly expressed, or even in the same post, the aim of sentiment analysis is to detect sentiment. To better comprehend what internet users are saying about a company’s goods and services, businesses employ natural language processing tools like sentiment analysis.

c. Text Classification – Text classification enables you to classify a document and organize it to make it easier to find the information you need or to carry out certain tasks. Spam screening in email is one example of how text categorization is used.

d. Virtual Assistants – These days, digital assistants like Google Assistant, Cortana, Siri, and Alexa play a significant role in our lives. Not only can we communicate with them, but they can also facilitate our life. They can assist us in making notes about our responsibilities, making calls for us, sending messages, and much more by having access to our data.

Natural Language Processing Class 10 Questions and Answers

3. What is Cognitive Behavioural Therapy (CBT)?
Answer – One of the most effective ways to deal with stress is cognitive behavioural therapy (CBT), which is popular since it is simple to apply to people and produces positive outcomes. Understanding a person’s behaviour and mentality in daily life is part of this therapy. Therapists assist clients in overcoming stress and leading happy lives with the aid of CBT.

4. What is Problem Scoping?
Answer – Understanding a problem and identifying numerous elements that have an impact on it help define the project’s purpose or objective. Who, What, Where, and Why are the 4Ws of problem scoping. These Ws make it easier and more effective to identify and understand the problem.

5. What is Data Acquisition?
Answer – We need to gather conversational data from people in order to decipher their setements and comprehend their meaning in order to grasp their feelings. This collection of information is known as Data Acquistion. Such information can be gathered in a variety of ways –
a. Surveys
b. Observing the therapist’s sessions
c. Databased available on the internet

Natural Language Processing Class 10 Questions and Answers

6. What is Data Exploration?
Answer – Once the textual information has been gathered using Data Acquistition, it must be cleaned up and processed before being delivered to the machine in a simpler form. As a result, the text is normalised using a number of processes, and the vocabulary is reduced to a minimum because the computer just needs the text’s main ideas rather than its grammar.

7. What is Data Modelling?
Answer – After the text has been normalised, an NLP-based AI model is then fed the data. Keep in mind that in NLP, data pre-processing is only necessary after which the data is supplied to the computer. There are numerous AI models that can be used, depending on the kind of chatbot we’re trying to create, to help us lay the groundwork for our project.

8. What is Data Evaluation?
Answer – The correctness of the trained model is determined based on how well the machine-generated answers match the user’s input is knwon as Data Evaluation. The chatbot’s proposed answers are contrasted with the correct answers to determine the model’s efficacy.

Natural Language Processing Class 10 Questions and Answers

9. What is Chatbot?
Answer – A chatbot is a piece of software or an agent with artificial intelligence that uses natural language processing to mimic a conversation with users or people. You can have the chat through a website, application, or messaging app. These chatbots, often known as digital assistants, can communicate with people verbally or via text.

The majority of organizations utilize AI chatbots, such the Vainubot and HDFC Eva chatbots, to give their clients virtual customer assistance around-the-clock.

Some of the example of Chatbot –
a. Mitsuku Bot
b. CleverBot
c. Jabberwacky
d. Haptik
e. Rose
f. Ochtbot

Natural Language Processing Class 10 Questions and Answers

10. Types of Chatbot?
Answer – There are two types of Chatbot –
a. Script Bot – An Internet bot, sometimes known as a web robot, robot, or simply bot, is a software programme that does automated operations (scripts) over the Internet, typically with the aim of simulating extensive human online activity like communicating.

b. Smart Bot – An artificial intelligence (AI) system that can learn from its surroundings and past experiences and develop new skills based on that knowledge is referred to as a smart bot. Smart bot that are intelligent enough can operate alongside people and learn from their actions.

11. Difference between human language vs computer language?
Answer – Although there is a significant difference between the languages, human language and computer language can be translated into one other very flawlessly. Human languages can be used in voice, writing, and gesture, whereas machine-based languages can only be used in written communication. A computer’s textual language can communicate with vocal or visual clues depending on the situation, as in AI chatbots with procedural animation and speech synthesis. But in the end, language is still written. The languages also have different meanings. Human languages are utilized in a variety of circumstances, including this blog post, whereas machine languages are almost solely used for requests, commands, and logic.

Natural Language Processing Class 10 Questions and Answers

12. What do you mean by Multiple Meanings of a word in Deep Learning?
Answer – Depending on the context, the term mouse can be used to refer to either a mammal or a computer device. Consequently, mouse is described as ambiguous. The Principle of Economical Versatility of Words states that common words have a tendency to acquire additional senses, which can create practical issues in subsequent jobs. Additionally, this meaning conflation has additional detrimental effects on correct semantic modelling, such as the pulling together in the semantic space of words that are semantically unrelated yet are comparable to distinct meanings of the same word.

13. What is Data Processing?
Answer – Making data more meaningful and informative is the effort of changing it from a given form to one that is considerably more useable and desired. This entire process can be automated using Machine Learning algorithms, mathematical modelling, and statistical expertise.

14. What is Text Normalisation?
Answer – The process of converting a text into a canonical (standard) form is known as text normalisation. For instance, the canonical form of the word “good” can be created from the words “gooood” and “gud.” Another case is the reduction of terms that are nearly identical, such as “stopwords,” “stop-words,” and “stop words,” to just “stopwords.”

We must be aware that we will be working on a collection of written text in this portion before we start. As a result, we will be analysing text from a variety of papers. This collection of text from all the documents is referred to as a corpus. We would perform each stage of Text Normalization and test them on a corpus in addition to going through them all.

Natural Language Processing Class 10 Questions and Answers

15. What is Sentence Segmentation in AI?
Answer – The challenge of breaking down a string of written language into its individual sentences is known as sentence segmentation. The method used in NLP to determine where sentences actually begin and end, or you can just say that this is how we divide a text into sentences. Sentence segmentation is the process in question. Using the spacy library, we implement this portion of NLP in Python.

16. What is Tokenisation in AI?
Answer – The challenge of breaking down a string of written language into its individual words is known as word tokenization (also known as word segmentation). Space is a good approximation of a word divider in English and many other languages that use some variation of the Latin alphabet.

17. What is purpose of Stopwords?
Answer – Stopwords are words that are used frequently in a corpus but provide nothing useful. Humans utilize grammar to make their sentences clear and understandable for the other person. However, grammatical terms fall under the category of stopwords because they do not add any significance to the information that is to be communicated through the statement. Stopword examples include –
a/ an/ and/ are/ as/ for/ it/ is/ into/ in/ if/ on/ or/ such/ the/ there/ to

Natural Language Processing Class 10 Questions and Answers

18. What is Stemming in AI?
Answer – The act of stripping words of their affixes and returning them to their original forms is known as stemming. The process of stemming can be carried out manually or by an algorithm that an AI system may use. Any inflected form that is encountered can be reduced to its root by using a variety of stemming techniques. A stemming algorithm can be created easily.

19. What is Lemmatization?
Answer – Stemming and lemmatization are alternate techniques to one another because they both function to remove affixes. However, lemmatization differs from both of them in that the word that results from the elimination of the affix (also known as the lemma) is meaningful.
Lemmatization takes more time to complete than stemming because it ensures that the lemma is a word with meaning.

Natural Language Processing Class 10 Questions and Answers

20. What is bag of Words?
Answer – Bag of Words is a model for natural language processing that aids in removing textual elements that can be used by machine learning techniques. We obtain each word’s occurrences from the bag of words and create the corpus’s vocabulary.
An approach to extracting features from text for use in modelling, such as with machine learning techniques, is known as a bag-of-words model, or BoW for short. The method is really straightforward and adaptable, and it may be applied in a variety of ways to extract features from documents.

21. What is TFIDF?
Answer – TF-IDF, which stands for term frequency-inverse document frequency, is a metric that is employed in the fields of information retrieval (IR) and machine learning to quantify the significance or relevance of string representations (words, phrases, lemmas, etc.) in a document among a group of documents (also known as a corpus).

22. What are the different applications of TFIDF?
Answer – TFIDF is commonly used in the Natural Language Processing domain. Some of its applications are:
a. Document classification -Helps in classifying the type and genre of a document.
b. Topic Modelling – It helps in predicting the topic for a corpus.
c. Information Retrieval System – To extract the important information out of a corpus.
d. Steop word filtering – Helps in removing the unnecessary words out of a text body.

Natural Language Processing Class 10 Questions and Answers

23. Write any two TFIDF application?
Answer – 1. Document Classification – Helps in classifying the type and genre of a document.
2. Topic Modelling – It helps in predicting the topic for a corpus.
3. Information Retrieval System – To extract the important information out of a corpus.
4. Stop word filtering – Helps in removing the unnecessary words out of a text body.

24. Write the steps necessary to implement the bag of words algorithm.
Answer – The steps to implement bag of words algorithm are as follows:
1. Text Normalisation: Collect data and pre-process it
2. Create Dictionary: Make a list of all the unique words occurring in the corpus.
3. Create document vectors: For each document in the corpus, find out how many times the word from the unique list of words has occurred.
4. Create document vectors for all the documents.

25. What is the purpose of confusion matrix? What does it serve?
Answer – The comparison between the prediction and reality’s outcomes is stored in the confusion matrix. We can determine variables like recall, precision, and F1 score, which are used to assess an AI model’s performance, from the confusion matrix.

26. How does the relationship between a word’s value and frequency in a corpus look like in the given graph?

Answer – The graph demonstrates the inverse relationship between word frequency and word value. The most frequent terms, such as stop words, are of little significance. The value of words increases as their frequency decreases. These words are referred to as precious or uncommon words. The least frequently occurring but most valuable terms in the corpus are those.

27. In data processing, define the term “Text Normalization.”
Answer – Text normalisation is the initial step in the data processing process. Text normalisation assists in reducing the complexity of the textual data to a point where it is comparable to the actual data. To lower the text’s normalisation level in this, we go through numerous procedures. We work with text from several sources, and the collective textual data from all the papers is referred to as a corpus.

Natural Language Processing Class 10 Questions and Answers

28. Explain the differences between lemmatization and stemming. Give an example to assist you explain.
Answer – Stemming is the process of stripping words of their affixes and returning them to their original form.
After the affix is removed during lemmatization, we are left with a meaningful word known as a lemma. Lemmatization takes more time to complete than stemming because it ensures that the lemma is a word with meaning.
The following example illustrates the distinction between stemming and lemmatization:

Caring >> Lemmatization >> Care
Caring >> Stemming >> Car

Natural Language Processing Class 10 Questions and Answers

29. Imagine developing a prediction model based on AI and deploying it to monitor traffic congestion on the roadways. Now, the model’s goal is to foretell whether or not there will be a traffic jam. We must now determine whether or not the predictions this model generates are accurate in order to gauge its efficacy. Prediction and Reality are the two conditions that we need to consider.

Today, traffic jams are a regular occurrence in our life. Every time you get on the road when you live in an urban location, you have to deal with traffic. Most pupils choose to take buses to school. Due to these traffic bottlenecks, the bus frequently runs late, making it impossible for the pupils to get to school on time.

Create a Confusion Matrix for the aforementioned scenario while taking into account all potential outcomes.

Answer –

Case 1: Is there a traffic Jam?
Prediction: Yes Reality: Yes
True Positive
Case 2: Is there a traffic Jam?
Prediction: No Reality: No
True Negative
Case 3: Is there a traffic Jam?
Prediction: Yes Reality: No
False Positive
Case 4: Is there a traffic Jam?
Prediction: No Reality: Yes
False Negative

Natural Language Processing Class 10 Questions and Answers

30. Make a 4W Project Canvas.

Risks will become more concentrated in a single network as more and more innovative technologies are used. In such cases, cybersecurity becomes incredibly complex and is no longer under the authority of firewalls. It won’t be able to recognise odd behaviour patterns, including data migration.
Consider how AI systems can sift through voluminous data to find user behaviour that is vulnerable. To explicitly define the scope, the method of data collection, the model, and the evaluation criteria, use an AI project cycle.

Answer – 

Employability skills Class 10 Notes

• Unit 1- Communication Skills Class 10 Notes
• Unit 2- Self-Management Skills Class 10 Notes
• Unit 3- Basic ICT Skills Class 10 Notes
• Unit 4- Entrepreneurial Skills Class 10 Notes
• Unit 5- Green Skills Class 10 Notes

Employability skills Class 10 MCQ

• Unit 1- Communication Skills Class 10 MCQ
• Unit 2- Self-Management Skills Class 10 MCQ
• Unit 3- Basic ICT Skills Class 10 MCQ
• Unit 4- Entrepreneurial Skills Class 10 MCQ
• Unit 5- Green Skills Class 10 MCQ

Employability skills Class 10 Questions and Answers

• Unit 1- Communication Skills Class 10 Questions and Answers
• Unit 2- Self-Management Skills Class 10 Questions and Answers
• Unit 3- Basic ICT Skills Class 10 Questions and Answers
• Unit 4- Entrepreneurial Skills Class 10 Questions and Answers
• Unit 5- Green Skills Class 10 Questions and Answers

Artificial Intelligence Class 10 Notes

• Unit 1 – Introduction to Artificial Intelligence Class 10 Notes
• Unit 2 – AI Project Cycle Class 10 Notes
• Unit 3 – Natural Language Processing Class 10 Notes
• Unit 4 – Evaluation Class 10 Notes
• Advanced Python Class 10 Notes
• Computer Vision Class 10 Notes

Artificial Intelligence Class 10 MCQ

• Unit 1 – Introduction to Artificial Intelligence Class 10 MCQ
• Unit 2 – AI Project Cycle Class 10 MCQ
• Unit 3 – Natural Language Processing Class 10 MCQ
• Unit 4 – Evaluation Class 10 MCQ

Artificial Intelligence Class 10 Questions and Answers

• Unit 1 – Introduction to Artificial Intelligence Class 10 Questions and Answers
• Unit 2 – AI Project Cycle Class 10 Questions and Answers
• Unit 3 – Natural Language Processing Class 10 Questions and Answers
• Unit 4 – Evaluation Class 10 Questions and Answers

Teachers and Examiners (CBSESkillEduction) collaborated to create the AI Project Cycle Class 10 Questions and Answers. All the important QA are taken from the NCERT Textbook Artificial Intelligence ( 417 ) class X.

AI Project Cycle Class 10 Questions and Answers

1. What stages of an AI project are there?
Answer – There are five different stages of AI Project.
Problem Scoping >> Data Acquisition >> Data Exploration >> Modelling >> Evaluation

2. What is problem Scoping?
Answer – The process through which student designers “figure out” the problem they need to solve is called problem scoping. It is the procedure used to identify the issue.

You establish the objective for your AI project by identifying the issue you hope to address. When problem scoping, we consider several factors that have an impact on the issue we’re trying to address to make the situation more evident.

AI Project Cycle Class 10 Questions and Answers

3. How you can figure out the data using problem scoping?
Answer –

a. You need to acquire data which will become the base of your project.
b. Collect data from various reliable and authentic sources
c. After exploring the patterns, you can decide upon the type of model you would build to achieve the goal.
d. You can test the selected models and figure out which is the most efficient one.
e. The most efficient model is now the base of your AI project and you can develop your algorithm around it
f. Once the modelling is complete, you now need to test your model on some newly fetched data. The results will help you in evaluating your model and improving it.

AI Project Cycle Class 10 Questions and Answers

4. What is Sustainable Development?

Answer – When all renewable resources are utilized properly, the variety of life on earth is conserved, and environmental harm is kept to a minimum for the benefit of future generations, this is considered sustainable development.

According to the Bruntland Commission Report from 1987, sustainable development refers to “development that satisfies present demands without compromising the ability of future generations to meet their own needs.”

AI Project Cycle Class 10 Questions and Answers

5. What are the goals of sustainable development?
Answer – There are 17 sustainable development goals announced by the United nations, aim to achieve these goals by the end of 2030 –
a. No Poverty
b. Zero Hunger
c. Good Health and Well-being
d. Quality Education
e. Gender Equality
f. Clean Water and Sanitation
g. Affordable and Clean Energy
h. Decent Work and Economic Growth
i. Industry, Innovation and Infrastructure
j. Reduced Inequality
k. Sustainable Cities and Communities
l. Responsible Consumption and Production
m. Climate Action
n. Life Below Water
o. Life on Land
p. Peace and Justice Strong Institutions
q. Partnerships to achieve the Goal

6. What is 4Ws Problem Canvas?
Answer – Who, What, Where, and Why are the 4Ws of problem scoping. These Ws aid in more accurate and effective problem identification and comprehension.
a. who : who is facing for problem who are the stakeholders of problem .
b. what: what is refer to a asking question .
c. where : where is refer to asking about the place where the person was going.
d. why: why is refer to a asking about the person like why are you asking question .

AI Project Cycle Class 10 Questions and Answers

7. Who are the stakeholders?
Answer – Stakeholders are people who are either actively involved in the project or who have interests that the project’s results might influence. Project managers, project sponsors, executives, clients, or users are typically included in this group.

9. What do you mean by Problem Statement Template?
Answer – An stakeholders can define and describe a problem by writing a summarize report called a problem statement. Its objective is to offer a comprehensive plan of action to address the issue and include suggestions for how those responsible can stop it from happening again in the future.

10. What is data Acquisition?
Answer – The process of gathering correct and trustworthy data to work with is known as data acquisition. The second stage of the project cycle is data acquisition, and for successful decision making, we must make sure the data is gathered from genuine and trustworthy sources.

AI Project Cycle Class 10 Questions and Answers

11. What is the difference between Training Data & Testing Data?
Answer – The datasets are divided into two groups in machine learning. The first subset, referred to as the training data, is a section of our actual dataset that is used to train a machine learning model. Second subset, referred to testing data, Once your machine learning model is built, you need unseen data to test your model. This data is called testing data.

Note – Training data use 80% of the whole data and testing data use 20%.

12. What is data features?
Answer – Data features refer to the type of data you want to collect.

AI Project Cycle Class 10 Questions and Answers

13. What are the various ways to collect data?
Answer – Various ways to collect the data is –
a. Surveys
b. Web Scraping
c. Sensors
d. Cameras
e. Observations
f. Application Program Interface (API)

AI Project Cycle Class 10 Questions and Answers

14. What is data exploration?
Answer – Data exploration is the process of displaying and detecting unique patterns and trends in data using tools and procedures. Data visualization and other complex statistical techniques can be used to do this.

15. What is data modelling?
Answer – Data modelling is the process of developing a visual representation of an entire information system or certain components of it. for example the development, training, and application of machine learning algorithms that simulate logical decision-making based on accessible facts are known as AI modelling.

16. Types of AI Modelling?
Answer – AI Models are classified into two type –
a. Learning Based
b. Rule Based

AI Project Cycle Class 10 Questions and Answers

17. What is Rule Based Approach?
Answer – When the developer sets the rules. The machine executes its duty in accordance with the rules or instructions specified by the developer.
A rule-based artificial intelligence (AI) system is one that aims to develop artificial intelligence (AI) by using a model that is exclusively based on predetermined rules.

18. What is Learning Based Approach?
Answer – AI modelling where the computer learns on its own. The AI model is trained on the data provided to it under the Learning Based technique, and after that, it is able to create a model that is flexible to the change in data.

AI Project Cycle Class 10 Questions and Answers

19. What are the different type of Learning based approach?
Answer – The learning based approach can be divided into three types –

a. Supervised Learning – In order for a computer to learn from data, it must have external supervision. This is known as supervised learning. We use the labelled dataset to train the supervised learning models. Supervised machine learning is a method for addressing two major issues: regression and classification.

b. Unsupervised Learning – This term refers to a sort of machine learning in which the machine can learn from the data on its own without any external supervision. The unlabelled dataset can be used to train the unsupervised models. These are employed in order to address the Association and Clustering issues.

c. Reinforcement Learning – Reinforcement learning is a learning process where an agent interacts with its environment by taking actions and learns through feedback. The agent receives feedback in the form of rewards; for example, he receives a positive reward for each good activity and a negative reward for each bad action. The agent is not under any oversight. Reinforcement learning makes use of the Q-Learning algorithm.

AI Project Cycle Class 10 Questions and Answers

20. Who many type of Supervised Learning models in AI?
Answer – There are two types of Supervised Learning model –
a. Classification – When the data is labeled-based categorized. For instance, under the grading system, students are categorized based on the grades they receive in relation to their exam marks.

b. Regression – Such models work on continuous data. 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.

AI Project Cycle Class 10 Questions and Answers

21. How many type of Unsupervised Learning model in AI?
Answer – There are two type of Unsupervised learning models in AI –
a. Clustering – refers to the unsupervised learning technique that can cluster the unknown data according to patterns or trends found in it. The developer may already be aware of the patterns noticed, or it may even generate some original patterns as a result.

b. Dimensionality Reduction – If you have a large number of features, it could be beneficial to minimise them using an unsupervised step before moving on to supervised steps. Numerous unsupervised learning techniques include a transform technique that can be used to lessen the dimensionality.

AI Project Cycle Class 10 Questions and Answers

22. What is Evaluation?
Answer – By feeding the test dataset into the model and comparing the outputs to the actual results, evaluation is the process of determining the dependability of any AI model. Depending on the kind of model and its intended use, many evaluation procedures may be used.

23. Give a brief introduction to the Turing test in AI?
Answer – One of the widely used intelligence tests in artificial intelligence is the Turing test. In the year 1950, Alan Turing developed the Turing test. A machine’s ability to think like a human is being tested in this experiment. This test states that a computer can only be considered intelligent if it can imitate human behaviour in specific situations.

In this test, there are three participants: a computer, a human responder, and a human interrogator. The interrogator’s job is to determine which response is coming from the machine based on the questions and responses.

24. What is overfitting? How can it be overcome in Machine Learning?
Answer – Overfitting in the model happens when the machine learning algorithm tries to include all of the data points and, as a result, includes noise as well. This overfitting problem causes the algorithm to display low bias but large output variance. One of the biggest problems with machine learning is overfitting.

AI Project Cycle Class 10 Questions and Answers

25. What is Expert System?
Answer – An expert system in artificial intelligence is a computer programme that mimics the capacity for judgement of a human expert. Expert systems are created to reason through knowledge bases that are primarily represented as if-then rules rather than through traditional procedural code.

26. What is the use of computer vision in AI?
Answer – Computers may be taught to understand and extract data from the visual environment, such as photographs, using an area of artificial intelligence called computer vision. Thus, computer vision makes use of AI technology to resolve challenging issues like image processing and object detection.

27. What is confusion matrix in ai?
Answer – An N x N matrix called a confusion matrix is used to assess the effectiveness of a classification model, where N is the total number of target classes. In the matrix, the actual goal values are contrasted with those that the machine learning model anticipated.

AI Project Cycle Class 10 Questions and Answers

28. What is F1 score in ai?
Answer – When data are unbalanced, such as when the number of cases belonging to one class greatly outnumbers those found in the other class, the F1 score is a popular performance metric for classification and is frequently selected over, for example, accuracy.

29. Why shouldn’t the training data be used for evaluation?

Answer – This is so that our model will always predict the right label for any point in the training set because it will just remember the entire training set.

AI Project Cycle Class 10 Questions and Answers

30. Give an example of a circumstance where a false positive would come at a high cost.

Answer – Let’s have a look at a model that can determine whether a message is spam or not. People would not read the letter if the model consistently predicted that it was spam, which could lead to the eventual loss of crucial information. Here, a false positive condition (predicting that a message is spam when it is not) would be expensive.

31. What is a confusion matrix? What is it used for?

Answer – The comparison between the prediction and reality’s outcomes is stored in the confusion matrix. We can determine variables like recall, precision, and F1 score, which are used to assess an AI model’s performance, from the confusion matrix.

Employability skills Class 10 Notes

• Unit 1- Communication Skills Class 10 Notes
• Unit 2- Self-Management Skills Class 10 Notes
• Unit 3- Basic ICT Skills Class 10 Notes
• Unit 4- Entrepreneurial Skills Class 10 Notes
• Unit 5- Green Skills Class 10 Notes

Employability skills Class 10 MCQ

• Unit 1- Communication Skills Class 10 MCQ
• Unit 2- Self-Management Skills Class 10 MCQ
• Unit 3- Basic ICT Skills Class 10 MCQ
• Unit 4- Entrepreneurial Skills Class 10 MCQ
• Unit 5- Green Skills Class 10 MCQ

Employability skills Class 10 Questions and Answers

• Unit 1- Communication Skills Class 10 Questions and Answers
• Unit 2- Self-Management Skills Class 10 Questions and Answers
• Unit 3- Basic ICT Skills Class 10 Questions and Answers
• Unit 4- Entrepreneurial Skills Class 10 Questions and Answers
• Unit 5- Green Skills Class 10 Questions and Answers

Artificial Intelligence Class 10 Notes

• Unit 1 – Introduction to Artificial Intelligence Class 10 Notes
• Unit 2 – AI Project Cycle Class 10 Notes
• Unit 3 – Natural Language Processing Class 10 Notes
• Unit 4 – Evaluation Class 10 Notes
• Advanced Python Class 10 Notes
• Computer Vision Class 10 Notes

Artificial Intelligence Class 10 MCQ

• Unit 1 – Introduction to Artificial Intelligence Class 10 MCQ
• Unit 2 – AI Project Cycle Class 10 MCQ
• Unit 3 – Natural Language Processing Class 10 MCQ
• Unit 4 – Evaluation Class 10 MCQ

Artificial Intelligence Class 10 Questions and Answers

• Unit 1 – Introduction to Artificial Intelligence Class 10 Questions and Answers
• Unit 2 – AI Project Cycle Class 10 Questions and Answers
• Unit 3 – Natural Language Processing Class 10 Questions and Answers
• Unit 4 – Evaluation Class 10 Questions and Answers

Teachers and Examiners (CBSESkillEduction) collaborated to create the CBSE Class 10 Artificial Intelligence Questions and Answers. All the important MCQs are taken from the NCERT Textbook Artificial Intelligence ( 417 ) class X.

CBSE Class 10 Artificial Intelligence Questions and Answers

1. What is Intelligence?

Answer – Machines that can simplify human life have been created by humans. Machines are designed to complete jobs that are either time-consuming or too laborious for people to complete.
Therefore, machines assist us by performing tasks for us, dividing our workload, and making it simpler for us to achieve these objectives.

2. What is Artificial Intelligence?

Answer – The replication of human intelligence functions by machines, particularly computer systems, is known as artificial intelligence. Expert systems, natural language processing, speech recognition, and machine vision are some examples of specific AI applications.

CBSE Class 10 Artificial Intelligence Questions and Answers

3. What are the different abilities that are involved in Intelligence?

Answer – The abilities that are involved in Intelligence are –
a. Musical Intelligence
b. Mathematical Logic Intelligence
c. Linguistic Intelligence
d. Spatial Visual Intelligence
e. Kinaesthetic Intelligence
f. Existential Intelligence
g. Intrapersonal Intelligence
h. Interpersonal Intelligence
i. Naturalist Intelligence

CBSE Class 10 Artificial Intelligence Questions and Answers

4. How do you make decisions?

Answer – The basis for decision-making depends on the information that is available and how we perceive and comprehend it. Without information, we are unable to make “excellent” decisions because we are forced to deal with unknown variables and encounter uncertainty, which forces us to make irrational assumptions, flip coins, or roll dice. Knowing something about a situation, having experience with it, or having insights into it let us imagine possible outcomes. and how we might accomplish or prevent those results.

CBSE Class 10 Artificial Intelligence Questions and Answers

5. What are the different Applications of Artificial Intelligence?

Answer – Real-time language translators, weather predictions, the first humanoid robot clever enough to obtain citizenship, and biometric security systems like the face locks on our phones! This all are AI Application.

Let see some of the important AI application –

a. Google – We use Google to search the internet without realizing how effectively it always provides us with precise responses. It not only quickly returns the results of our search, but it also advises and corrects the grammar of our written words.

b. Hey Siri – These days, we have personal assistants that respond to a single command and perform numerous tasks. Several popular voice assistants that are an integral component of our digital devices are Alexa, Google Assistant, Cortana, and Siri.

c. FIFA Sports – AI has significantly improved the gaming experience. Many modern video games are supported by artificial intelligence (AI), which improves graphics, creates new challenges for players, etc.

d. Amazon – AI has taken care of our habits, likes, and dislikes in addition to making our lives easier. Because of this, services like Netflix, Amazon, Spotify, and YouTube, among others, display recommendations based on our preferences.

e. Social Media – The recommendations, however, go beyond simply reflecting our preferences; they also take into account our desire to interact with friends via social media networks like Facebook and Instagram. Additionally, they provide us personalized notifications about our online buying information, construct playlists automatically based on our demands, and more.

f. Chatbot – Our health is also being tracked by AI. There are many chatbots and other health apps available that continuously track their users’ physical and emotional wellbeing.

CBSE Class 10 Artificial Intelligence Questions and Answers

6. What is Machine Learning?

Answer – It is a branch of artificial intelligence that allows robots to get better at tasks over time (data). The goal of machine learning is to give computers the ability to learn on their own utilizing the supplied data and arrive at reliable predictions and decisions.

7. What is Deep Learning?

Answer – Software can use it to teach itself how to carry out tasks using enormous volumes of data. Massive volumes of data are used to train the machine in deep learning, allowing it to learn from the data. These devices possess the intelligence to create algorithms on their own.

The most sophisticated type of artificial intelligence among these three is deep learning. The next stage is intermediately intelligent machine learning, and artificial intelligence encompasses all ideas and techniques that, in some way or another, approximate human intelligence.

CBSE Class 10 Artificial Intelligence Questions and Answers

8. What is AI Domain?

Answer – The training an artificial intelligence receives determines how intelligent it becomes. Datasets are fed into the computer during training. The data given into the AI algorithm varies depending on the applications for which it is designed. AI models can be roughly divided into three categories based on the type of data they are fed, including:
a. Data Science
b. Computer Vision
c. Natural Language Processing

CBSE Class 10 Artificial Intelligence Questions and Answers

9. What is the purpose of Data Science in AI?

Answer – Data sciences is an area of AI that deals with data systems and processes. In this area, a system gathers a lot of data, maintains data sets, and extrapolates meaning from the data.
The information extracted through data science can be used to make a decision about it.
Example of Data Science – Price Comparison Websites

CBSE Class 10 Artificial Intelligence Questions and Answers

10. What is Computer Vision?

Answer – The field of artificial intelligence known as CV describes a machine’s capacity to gather and analyse visual data before making predictions about it. Image acquisition, screening, analysis, identification, and information extraction are all part of the process. Computers can comprehend any visual content and respond appropriately thanks to this thorough processing.

Example of Computer Vision – Self-Driving cars/ Automatic Cars / Face Lock in Smartphones

CBSE Class 10 Artificial Intelligence Questions and Answers

11. What is the purpose of NLP?

Answer – “Natural Language Processing,” or NLP, is concerned with how computers and people interact while utilizing natural language. Natural language processing (NLP), which aims to extract information from spoken and written words using algorithms, refers to language that is spoken and written by people.
Example of NLP – Email filters / Smart assistants

CBSE Class 10 Artificial Intelligence Questions and Answers

12. What is AI Ethics?

Answer – AI ethics is a set of moral guidelines and methods meant to guide the creation and ethical application of artificial intelligence technologies. Organizations are beginning to create AI codes of ethics as AI has become ingrained in goods and services.

CBSE Class 10 Artificial Intelligence Questions and Answers

13. What is Data Privacy in AI?

Answer – Data privacy is the ability to manage how our digital data is collected, used, and shared by various parties. Artificial intelligence is becoming more and more embedded into every part of our life as technology improves.

Data is the center of the artificial intelligence universe. Every business, no matter how big or little, is collecting data from as many sources as they can. The fact that more than 70% of the data acquired to date was just gathered in the previous three years demonstrates how crucial data has grown in recent years.

CBSE Class 10 Artificial Intelligence Questions and Answers

14. What is a AI Bias?

Answer – A occurrence known as machine learning bias, also known as algorithm bias or AI bias, is when an algorithm generates results that are systematically biassed as a result of false assumptions made during the machine learning process.

15. Why do we need Artificial Intelligence?

Answer – Artificial intelligence aims to build machines that are intelligent and can behave like people. In the modern world, AI is required to solve complicated problems, improve our daily lives by automating mundane operations, save labor, and carry out a wide range of other duties.

CBSE Class 10 Artificial Intelligence Questions and Answers

16. What is Deep Learning, and how is it used in real-world?

Answer – A subtype of machine learning called “deep learning” imitates how the human brain functions. It is modelled after the neurons found in the human brain and uses neural networks to tackle challenging real-world issues. Deep neural learning or the deep neural network are other names for it.

Deep learning has some practical applications, including:
a. Adding color to the black-and-white pictures
b. visual computing
c. text production
d. Robots with deep learning, etc.

CBSE Class 10 Artificial Intelligence Questions and Answers

17. Which programming language is used for AI?

Answer – The top five programming languages used most frequently for creating artificial intelligence are listed below:
a. Python
b. Java
c. Lisp
d. R
e. Prolog

18. What is the intelligent agent in AI, and where are they used?

Answer – Any autonomous entity that uses sensors to detect its surroundings and actuators to act on it might be considered an intelligent agent.

The following applications of AI make use of these intelligent agents:
a. Information Access and Navigations such as Search Engine
b. Repetitive Activities
c. Domain Experts
d. Chatbots, etc.

19. How is machine learning related to AI?

Answer – A subfield or subset of artificial intelligence is machine learning. It is a method of obtaining AI. Since these are distinct ideas, the relationship between them might be stated as “AI uses many machine learning concepts and techniques to solve complicated issues.”

CBSE Class 10 Artificial Intelligence Questions and Answers

20. What is the use of computer vision in AI?

Answer – Computers may be taught to understand and extract data from the visual environment, such as photographs, using an area of artificial intelligence called computer vision. Thus, computer vision makes use of AI technology to resolve challenging issues like image processing and object detection.

21. What are some misconceptions about AI?

Answer – Since the beginning of its development, artificial intelligence has been the subject of many myths. The following list includes a few of these myths:

a. AI does not require humans – The first false assumption regarding artificial intelligence is that it does not require humans. But in truth, every AI-based system still depends on people in some way and will continue to do so. For instance, human data collection is necessary to learn about the data.

b. AI will take your job – One of the major misconceptions is that AI would eliminate most occupations, but in truth, it is opening up more options for people to find new employment.

c. AI is harmful to people – Although strong or super AI, which is intelligent enough to outsmart people, has not yet been developed, AI is nevertheless potentially harmful to people. If it is not used improperly, any strong technology cannot be dangerous.

22. What is a Chatbot?

Answer – A chatbot is a piece of software or an agent with artificial intelligence that uses natural language processing to mimic a conversation with users or people. You can have the chat through a website, application, or messaging app. These chatbots, often known as digital assistants, can communicate with people verbally or via text.

CBSE Class 10 Artificial Intelligence Questions and Answers

22. What are the different areas where AI has a great impact?

Answer – The areas listed below are ones where AI has a significant impact:
a. Autonomous Transportation
b. Education-system powered by AI.
c. Healthcare
d. Predictive Policing
e. Space Exploration
f. Entertainment, etc.

23. What exactly is machine learning? Include 2 examples of how machine learning is used in everyday life.

Answer – Machine learning is a branch of artificial intelligence that enables machines to get better at tasks over time (data). Making correct predictions and decisions is the goal of machine learning, which aims to give machines the ability to learn on their own using the supplied data.

Snapchat filters and the Netflix recommendation engine both use machine learning.

CBSE Class 10 Artificial Intelligence Questions and Answers

24. Give the names of any four natural language processing apps that are used in real life situations.

Answer – the four natural language processing apps used in real life are –
a. Automatic Summarization,
b. Sentiment Analysis,
c. Text classification,
d. Virtual Assistants

25. Categorize the following into data sciences, machine learning, computer vision, and NLP.
Our lives are now more convenient thanks to recent technology developments. People who are not tech adept have benefited greatly from Google Home, Alexa, and Siri. Facelock and facial recognition features have increased the security of our devices. These developments have also helped to make our demands more accessible and practical. These days, you can even use price comparison websites to check costs and chatbots to order groceries online.
Did you know that you can even predict how you will look as you age? This is now feasible thanks to Snapchat filters and Facebook!

Answer –
a. Alexa, Siri-NLP, Facial Recognition – Computer Vision
b. Facelock – Computer Vision
c. Price comparison websites – Data Sciences
d. Chatbots – NLP
e. Facebook -NLP
f. Snapchat Filters – Machine Learning

CBSE Class 10 Artificial Intelligence Questions and Answers

26. Give some example of NLP applications (Natural Language Processing).

Answer –
a. Automatic Summarization – Automatic summarization is useful for gathering data from social media and other online sources as well as for summarizing the significance of papers and other information.

b. Sentiment Analysis – This technique identifies sentiment in a post, or even within a single post, where emotion is not always conveyed overtly.

c. Text classification – Text categorization allows you to add predetermined categories to a document and organize it to make it easier to find the information you need or to carry out certain tasks.

d. Virtual assistants – Using speech recognition, virtual assistants can understand our speech in addition to recognizing it.

Employability skills Class 10 Notes

• Unit 1- Communication Skills Class 10 Notes
• Unit 2- Self-Management Skills Class 10 Notes
• Unit 3- Basic ICT Skills Class 10 Notes
• Unit 4- Entrepreneurial Skills Class 10 Notes
• Unit 5- Green Skills Class 10 Notes

Employability skills Class 10 MCQ

• Unit 1- Communication Skills Class 10 MCQ
• Unit 2- Self-Management Skills Class 10 MCQ
• Unit 3- Basic ICT Skills Class 10 MCQ
• Unit 4- Entrepreneurial Skills Class 10 MCQ
• Unit 5- Green Skills Class 10 MCQ

Employability skills Class 10 Questions and Answers

• Unit 1- Communication Skills Class 10 Questions and Answers
• Unit 2- Self-Management Skills Class 10 Questions and Answers
• Unit 3- Basic ICT Skills Class 10 Questions and Answers
• Unit 4- Entrepreneurial Skills Class 10 Questions and Answers
• Unit 5- Green Skills Class 10 Questions and Answers

Artificial Intelligence Class 10 Notes

• Unit 1 – Introduction to Artificial Intelligence Class 10 Notes
• Unit 2 – AI Project Cycle Class 10 Notes
• Unit 3 – Natural Language Processing Class 10 Notes
• Unit 4 – Evaluation Class 10 Notes
• Advanced Python Class 10 Notes
• Computer Vision Class 10 Notes

Artificial Intelligence Class 10 MCQ

• Unit 1 – Introduction to Artificial Intelligence Class 10 MCQ
• Unit 2 – AI Project Cycle Class 10 MCQ
• Unit 3 – Natural Language Processing Class 10 MCQ
• Unit 4 – Evaluation Class 10 MCQ

Artificial Intelligence Class 10 Questions and Answers

• Unit 1 – Introduction to Artificial Intelligence Class 10 Questions and Answers
• Unit 2 – AI Project Cycle Class 10 Questions and Answers
• Unit 3 – Natural Language Processing Class 10 Questions and Answers
• Unit 4 – Evaluation Class 10 Questions and Answers

Teachers and Examiners (CBSESkillEduction) collaborated to create the Evaluation Class 10 AI MCQ. All the important MCQs are taken from the NCERT Textbook Artificial Intelligence ( 417 ) class X.

Evaluation Class 10 AI MCQ

1. ___________ is the process of understanding the reliability of any AI model, based on outputs by feeding
test dataset into the model and comparing with actual answers.
a. Evaluation 
b. Problem Scoping
c. Data acquisition
d. Data Exploration

Evaluation Class 10 AI MCQ

2. If model will simply remember the whole training set, and will therefore always predict the correct label for any point in the training set. This is known as ____________.
a. Overfitting 
b. Overriding
c. Over remembering
d. None of the above

Evaluation Class 10 AI MCQ

3. The result of comparison between the prediction and reality can be recorded in what we call the __________.
a. Overfitting
b. Problem Scoping
c. Confusion Matrix 
d. Data acquisition

4. The _____________ allows us to understand the prediction results.
a. Overfitting
b. Problem Scoping
c. Confusion Matrix 
d. Data acquisition

5. _________ is defined as the percentage of correct predictions out of all the observations.
a. Overfitting
b. Accuracy
c. Confusion Matrix
d. Data acquisition

Evaluation Class 10 AI MCQ

6. _______ is defined as the percentage of true positive cases versus all the cases where the prediction is true.
a. Overfitting
b. Accuracy
c. Precision 
d. Data acquisition

7. ___________ can be defined as the fraction of positive cases that are correctly identified.
a. Recall 
b. Accuracy
c. Precision
d. Data acquisition

8. ___________ can be defined as the measure of balance between precision and recall.
a. Recall
b. Accuracy
c. Precision
d. F1 Score 

Employability skills Class 10 Notes

• Unit 1- Communication Skills Class 10 Notes
• Unit 2- Self-Management Skills Class 10 Notes
• Unit 3- Basic ICT Skills Class 10 Notes
• Unit 4- Entrepreneurial Skills Class 10 Notes
• Unit 5- Green Skills Class 10 Notes

Employability skills Class 10 MCQ

• Unit 1- Communication Skills Class 10 MCQ
• Unit 2- Self-Management Skills Class 10 MCQ
• Unit 3- Basic ICT Skills Class 10 MCQ
• Unit 4- Entrepreneurial Skills Class 10 MCQ
• Unit 5- Green Skills Class 10 MCQ

Employability skills Class 10 Questions and Answers

• Unit 1- Communication Skills Class 10 Questions and Answers
• Unit 2- Self-Management Skills Class 10 Questions and Answers
• Unit 3- Basic ICT Skills Class 10 Questions and Answers
• Unit 4- Entrepreneurial Skills Class 10 Questions and Answers
• Unit 5- Green Skills Class 10 Questions and Answers

Artificial Intelligence Class 10 Notes

• Unit 1 – Introduction to Artificial Intelligence Class 10 Notes
• Unit 2 – AI Project Cycle Class 10 Notes
• Unit 3 – Natural Language Processing Class 10 Notes
• Unit 4 – Evaluation Class 10 Notes
• Advanced Python Class 10 Notes
• Computer Vision Class 10 Notes

Artificial Intelligence Class 10 MCQ

• Unit 1 – Introduction to Artificial Intelligence Class 10 MCQ
• Unit 2 – AI Project Cycle Class 10 MCQ
• Unit 3 – Natural Language Processing Class 10 MCQ
• Unit 4 – Evaluation Class 10 MCQ

Artificial Intelligence Class 10 Questions and Answers

• Unit 1 – Introduction to Artificial Intelligence Class 10 Questions and Answers
• Unit 2 – AI Project Cycle Class 10 Questions and Answers
• Unit 3 – Natural Language Processing Class 10 Questions and Answers
• Unit 4 – Evaluation Class 10 Questions and Answers

Teachers and Examiners (CBSESkillEduction) collaborated to create the Natural Language Processing Class 10 MCQ. All the important MCQs are taken from the NCERT Textbook Artificial Intelligence ( 417 ) class X.

Natural Language Processing Class 10 MCQ

1. NLP stands for _________.
a. Natural Language Processing 
b. Nature Language Processing
c. None Language Processing
d. None of the above

2. ___________, is the sub-field of AI that is focused on enabling computers to understand and process human languages.
a. Natural Language Processing 
b. Data Science
c. Computer Vision
d. None of the above

3. __________ is the sub-field of AI that make the interactions between computers and human (natural) languages
a. Natural Language Processing 
b. Data Science
c. Computer Vision
d. None of the above

4. Which of the games below is related to natural language processing?
a. Voice Assistants
b. Chatbots
c. Mystery Animal 
d. Grammar Checkers

5. Applications of Natural Language Processing
a. Automatic Summarization
b. Sentiment Analysis
c. Text Classification
d. All of the above 

6. ___________ Information overload is a real problem when we need to access a specific, important piece of information from a huge knowledge base.
a. Automatic Summarization 
b. Sentiment Analysis
c. Text Classification
d. All of the above

7. ___________ 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.
a. Automatic Summarization 
b. Sentiment Analysis
c. Text Classification
d. All of the above

8. 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.
a. Automatic Summarization
b. Sentiment Analysis 
c. Text Classification
d. All of the above

9. Companies use Natural Language Processing applications, such as _________, to identify opinions and sentiment online to help them understand what customers think about their products and services
a. Automatic Summarization
b. Sentiment Analysis 
c. Text Classification
d. All of the above

10. ___________ makes it possible to assign predefined categories to a document and organize it to help you find the information you need or simplify some activities.
a. Automatic Summarization
b. Sentiment Analysis
c. Text Classification 
d. All of the above

11. __________ device helps to communicate with humans and abilities to make humans lives easier.
a. Google Assistant
b. Cortana
c. Siri
d. All of the above 

12. _____________ is all about how machines try to understand and interpret human language and operate accordingly.
a. Natural Language Processing 
b. Data Science
c. Computer Vision
d. None of the above

13. By dividing up large problems into smaller ones, ____________ aims to help you manage them in a more constructive manner.
a. CDP
b. CBT 
c. CSP
d. CLP

14. CBT stands for ____________.
a. Common Behavioural Therapy (CBT)
b. Cognitive Behavioural Therapy (CBT) 
c. Connection Behavioural Therapy (CBT)
d. None of the above

15. Cognitive behavioural Therapy includes __________.
a. Your Thoughts
b. Your Behaviors
c. Your Emotions
d. All of the above 

16. ________ is considered to be one of the best methods to address stress as it is easy to implement on people and also gives good results.
a. Common Behavioural Therapy (CBT)
b. Cognitive Behavioural Therapy (CBT) 
c. Connection Behavioural Therapy (CBT)
d. None of the above

17. ____________ by collecting data from various reliable and authentic sources.
a. Data Acquisition 
b. Database
c. Data Mining
d. None of the above

18. Once the textual data has been collected, it needs to be processed and cleaned so that an easier version can be sent to the machine. This is known as __________.
a. Data Acquisition
b. Data Exploration 
c. Data Mining
d. None of the above

19. Once the text has been normalized, it is then fed to an NLP based AI model. Note that in NLP, modelling requires data pre-processing only after which the data is fed to the machine.
a. Data Acquisition
b. Modelling 
c. Data Mining
d. None of the above

20. The model trained is then evaluated and the accuracy for the same is generated on the basis of the
relevance of the answers which the machine gives to the user’s responses.
a. Data Acquisition
b. Modelling
c. Evaluation 
d. None of the above

21. One of the most common applications of Natural Language Processing is a chatbot, give some examples of chatbots __________.
a. Mitsuku Bot
b. CleverBot
c. Jabberwacky
d. All of the above 

22. There are ______ different types of chatbots.
a. 2 
b. 3
c. 4
d. 5

23. Which of the following is related to chatbots.
a. Script-bot
b. Smart-bot
c. Both a) and b) 
d. None of the above

24. _______ bots work around a script which is programmed in them.
a. Script-bot 
b. Smart-bot
c. Both a) and b)
d. None of the above

25. ________ work on bigger databases and other resources directly.
a. Script-bot
b. Smart-bot 
c. Both a) and b)
d. None of the above

26. ___________ helps in cleaning up the textual data in such a way that it comes down to a level where its complexity is lower than the actual data.
a. Speech Normalization
b. Text Normalization 
c. Visual Normalization
d. None of the above

27. ________ the whole corpus is divided into sentences. Each sentence is taken as a different data so now the whole corpus gets reduced to sentences.
a. Sentence Normalization
b. Sentence Segmentation 
c. Sentence Tokenization
d. All of the above

28. Under __________, every word, number and special character is considered separately and each of them is now a separate token.
a. Tokenization 
b. Token normalization
c. Token segmentation
d. All of the above

29. In Tokenization each sentence is divided into _________.
a. Block
b. Tokens 
c. Parts
d. None of the above

30. __________ are the words which occur very frequently in the corpus but do not add any value to it.
a. Tokens
b. Words
c. Stopwords 
d. None of the above

31. Stopwords are the words which occur very frequently in the corpus but do not add any value to it. for example_________.
a. Grammatical words 
b. Simple words
c. Complex words
d. All of the above

32. Give the example of stop words __________.
a. an
b. and
c. are
d. All of the above 

33. The machine does not consider ___________words as same words because of different cases.
a. Upper case
b. Lower case
c. Case sensitivity 
d. None of the above

34. ___________ is the process in which the affixes of words are removed and the words are converted to their base form.
a. Stemming 
b. Stopwords
c. Case-sensitivity
d. All of the above

35. Stemming and lemmatization both are _________ processes.
a. Same process
b. Alternative process 
c. Other process
d. All of the above

36. ________ makes sure that lemma is a word with meaning and hence it takes a longer time to execute than stemming.
a. Stopwords
b. Stemming
c. Lemmatization 
d. Token normalization

37. ___________ is a Natural Language Processing model which helps in extracting features out of the text which can be helpful in machine learning algorithms.
a. Bag of Words 
b. Big Words
c. Best Words
d. All of the above

38. Which steps we have to approach to implement the bag of words algorithm.
a. Text Normalization
b. Create Dictionary
c. Create Document Vectors
d. All of the above 

39. ________ identify each document in the corpus, find out how many times the word from the unique list of words has occurred.
a. Text Normalization
b. Create Dictionary
c. Document Vectors 
d. All of the above

40. TFIDF stands for ___________.
a. Team Frequency and Inverse Document Frequency
b. Term Frequency and Inverse Document Frequency 
c. Top Frequency and Inverse Document Frequency
d. Table Frequency and Inverse Document Frequency

41. Applications of TFIDF are ___________.
a. Document Classification
b. Topic Modelling
c. Information Retrieval System and Stop word filtering
d. All of the above 

Employability skills Class 10 Notes

• Unit 1- Communication Skills Class 10 Notes
• Unit 2- Self-Management Skills Class 10 Notes
• Unit 3- Basic ICT Skills Class 10 Notes
• Unit 4- Entrepreneurial Skills Class 10 Notes
• Unit 5- Green Skills Class 10 Notes

Employability skills Class 10 MCQ

• Unit 1- Communication Skills Class 10 MCQ
• Unit 2- Self-Management Skills Class 10 MCQ
• Unit 3- Basic ICT Skills Class 10 MCQ
• Unit 4- Entrepreneurial Skills Class 10 MCQ
• Unit 5- Green Skills Class 10 MCQ

Employability skills Class 10 Questions and Answers

• Unit 1- Communication Skills Class 10 Questions and Answers
• Unit 2- Self-Management Skills Class 10 Questions and Answers
• Unit 3- Basic ICT Skills Class 10 Questions and Answers
• Unit 4- Entrepreneurial Skills Class 10 Questions and Answers
• Unit 5- Green Skills Class 10 Questions and Answers

Artificial Intelligence Class 10 Notes

• Unit 1 – Introduction to Artificial Intelligence Class 10 Notes
• Unit 2 – AI Project Cycle Class 10 Notes
• Unit 3 – Natural Language Processing Class 10 Notes
• Unit 4 – Evaluation Class 10 Notes
• Advanced Python Class 10 Notes
• Computer Vision Class 10 Notes

Artificial Intelligence Class 10 MCQ

• Unit 1 – Introduction to Artificial Intelligence Class 10 MCQ
• Unit 2 – AI Project Cycle Class 10 MCQ
• Unit 3 – Natural Language Processing Class 10 MCQ
• Unit 4 – Evaluation Class 10 MCQ

Artificial Intelligence Class 10 Questions and Answers

• Unit 1 – Introduction to Artificial Intelligence Class 10 Questions and Answers
• Unit 2 – AI Project Cycle Class 10 Questions and Answers
• Unit 3 – Natural Language Processing Class 10 Questions and Answers
• Unit 4 – Evaluation Class 10 Questions and Answers

Teachers and Examiners (CBSESkillEduction) collaborated to create the AI Project Cycle Class 10 MCQ. All the important MCQs are taken from the NCERT Textbook Artificial Intelligence ( 417 ) class X.

AI Project Cycle Class 10 MCQ

1. The AI Project Cycle mainly has __________.
a. 2 Stages
b. 3 Stages
c. 4 Stages
d. 5 Stages

2. What are the various parameters which affect the problem ____________.
a. You need to acquire data which will become the base of your project
b. You go for data acquisition by collecting data from various reliable and authentic sources.
c. After exploring the patterns, you can decide upon the type of model you would build to achieve the goal.
d. All of the above 

3. You need to __________ which will become the base of your project as it will help you in understanding what the parameters that are related to problem scoping are.
a. Acquire Data 
b. Database
c. Data Mining
d. None of the above

4. ____________ by collecting data from various reliable and authentic sources.
a. Data Acquisition 
b. Database
c. Data Mining
d. None of the above

5. Once the __________ is complete, you now need to test your model on some newly fetched data.
a. Data Acquisition
b. Modelling 
c. Data Mining
d. None of the above

6. The Sustainable Development Goals aim is to achieve by the end of year_______.
a. 2025
b. 2030 
c. 2035
d. 2040

7. The ________ Problem canvas helps in identifying the key elements related to the problem.
a. 4Ws 
b. 6Ws
c. 2Ws
d. 3Ws

8. _________ are the people who face this problem and would be benefited with the solution.
a. Key Persons
b. Stakeholders 
c. End user
d. None of the above

9. The ________ block helps in analyzing the people getting affected directly or indirectly due to it.
a. Who 
b. What
c. Where
d. Why

10. ________ helps to determine the nature of the problem.
a. Who
b. What 
c. Where
d. Why

11. “What” block helps to gather evidence from __________ to prove that the problem you have selected actually exists.
a. Media
b. Announcements
c. Newspaper & Articles
d. All of the above 

12. “Where” block will help you look into the situation in which the ___________where it is prominent.
a. Problem arises
b. The context of it
c. The locations
d. All of the above 

13. In “Why” block canvas, Which of the following canvases is the base of problem solving.
a. Who the people that would be benefitted by the solution
b. What is to be solved
c. Where will the solution be deployed
d. All of the above 

14. After filling the 4Ws Problem canvas, you now need to summarize all the cards into one _________.
a. Template 
b. Situation
c. Both a) and b)
d. None of the above

15. Templates help us to summarize all the key points into one single Template so that in future, whenever there is a need to look back at the basis of the problem, we can take a look at the __________ and understand the key elements of it.
a. Problem Solving Template
b. Problem Statement Template 
c. Problem Arising Template
d. None of the above

16. _________ helps to acquire data for the project.
a. Problem Scoping
b. Data Acquisition
c. Data Exploration
d. Data Evaluation

17. ___________ can be a piece of information or facts and statistics collected together for reference or analysis.
a. Database
b. Data
c. Data Type
d. None of the above

18. Whenever we want an AI project to be able to predict an output, we need to _______ it first using data.
a. Analyze
b. Train 
c. Explore
d. All of the above

19. You would feed the data into the machine. This is the data with which the machine can be trained. Now, once it is ready, it will predict his next data efficiently. This previous data is known as ___________.
a. Testing Data
b. Training Data 
c. Exploring Data
d. All of the above

20. You would feed the data into the machine. This is the data with which the machine can be trained. Now, once it is ready, it will predict his next data efficiently. This next data is known as ___________.
a. Testing Data 
b. Training Data
c. Exploring Data
d. All of the above

21. For better efficiency of an AI project, the _________ needs to be relevant and authentic.
a. Testing Data
b. Training Data 
c. Exploring Data
d. All of the above

22. __________ refer to the type of data you want to collect.
a. Data features 
b. Exploring Data
c. Data Acquisition
d. All of the above

23. What are the different ways to collect data?
a. Web Scraping & API
b. Surveys & Sensors
c. Cameras & Observations
d. All of the above 

24. Sometimes, you use the internet and try to acquire data for your project from some random websites. Such data might not be authentic as its accuracy cannot be proved. Due to this, it becomes necessary
to find a ____________.
a. Reliable source 
b. Random source
c. Unauthorize source
d. All of the above

25. One of the most reliable and authentic sources of information where we can download the authentic data for our project are ____________.
a. Private websites
b. Government websites 
c. Personal websites
d. None of the above

26. Data is a complex entity – it is full of numbers and if anyone wants to make some sense out of it, they have to work some patterns out of it.
a. Data acquiring 
b. Data mining
c. Data analysis
d. None of the above

27. The __________ makes the data understandable for humans as we can discover trends and patterns out of it.
a. Random Data
b. Graphical Representation 
c. Unstructured Data
d. None of the above

28. AI models can be classified as _________.
a. Learning Based
b. Rule Based
c. Both a) and b) 
d. None of the above

29. Learning Based models can be classified as __________.
a. Machine Learning
b. Deep Learning
c. Both a) and b) 
d. None of the above

30. AI modelling where the rules are defined by the developer is known as __________.
a. Rule Based Approach 
b. Learning based Approach
c. Both a) and b)
d. None of the above

31. _______ which tells us about the conditions on the basis of which we can decide
a. Dataset 
b. Rule Based
c. Learning based
d. None of the above

32. Learning based approaches are divided into _______ parts.
a. 2
b. 3 
c. 4
d. 5

33. Which one of the following is correct for Learning based approach?
a. Supervised Learning
b. Unsupervised Learning
c. Reinforcement Learning
d. All of the above 

34. In a _________ model, the dataset which is fed to the machine is labeled.
a. Supervised Learning 
b. Unsupervised Learning
c. Reinforcement Learning
d. All of the above

35. What are the different types of supervised learning?
a. Classification
b. Regression
c. Both a) and b) 
d. None of the above

36. Where the data is classified according to the labels is known as ________.
a. Classification 
b. Regression
c. Both a) and b)
d. None of the above

37. _________ models work on continuous data.
a. Classification
b. Regression 
c. Both a) and b)
d. None of the above

38. An ___________ model works on an unlabeled dataset.
a. Unsupervised learning 
b. Supervised learning
c. Reinforcement Learning
d. All of the above

39. The ______________ 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.
a. Unsupervised learning 
b. Supervised learning
c. Reinforcement Learning
d. All of the above

40. Unsupervised learning models are divided into _________ categories.
a. 5
b. 4
c. 3
d. 2 

41. Which categories belong to Unsupervised learning.
a. Clustering
b. Dimensionality Reduction
c. Both a) and b) 
d. None of the above

42. Unsupervised learning algorithm which can cluster the unknown data according to the patterns or trends identified out of it is known as ___________.
a. Clustering 
b. Dimensionality Reduction
c. Both a) and b)
d. None of the above

43. We humans are able to visualize up to 3-Dimensions only but according to a lot of theories and algorithms, there are various entities which exist beyond 3-Dimensions.
a. Clustering
b. Dimensionality Reduction 
c. Both a) and b)
d. None of the above

44. In Unsupervised learning models, if we need to reduce their dimension, which algorithm do we have to use?
a. Supervised algorithm
b. Dimensionality reduction algorithm 
c. Clustering algorithm
d. None of the above

45. _________ helps to test data so that one can calculate the efficiency and performance of the model.
a. Accuracy
b. Evaluation 
c. Precision
d. None of the above

46. Efficiency of the model is calculated on the basis of which parameters.
a. F1 Score >> Recall >> Precision >> Accuracy
b. Accuracy >> Precision >> Recall >> F1 Score 
c. Precision >> Accuracy >> F1 Score >> Recall
d. Recall >> Precision >> Accuracy >> F1 Score

47. ___________ are loosely modelled after how neurons in the human brain behave.
a. Neural networks 
b. Neural science
c. Neural Analysis
d. None of the above

48. The key advantage of ___________ are that they are able to extract data features automatically without
needing the input of the programmer.
a. Data Science
b. Deep Learning
c. Neural Network 
d. All of the above

49. A __________ is essentially a system of organizing machine learning algorithms to perform certain tasks
a. Data Science
b. Deep Learning
c. Neural Network 
d. All of the above

50. A Neural Network is divided into multiple layers and each layer is further divided into several blocks called __________.
a. Nodes 
b. Connector
c. Terminal
d. All of the above

51. The first layer of a Neural Network is known as the __________.
a. Output Layer
b. Input Layer 
c. Hidden Layer
d. All of the above

52. The job of an ________ is to acquire data and feed it to the Neural Network.
a. Output Layer
b. Input Layer 
c. Neural Layer
d. All of the above

53. In Neural Network, The ________ are the layers in which the whole processing occurs.
a. Output Layer
b. Input Layer
c. Hidden Layer 
d. All of the above

54. Hidden Layers in Neural Network means.
a. Layers are hidden
b. Not visual to the user
c. Both a) and b) 
d. None of the above

55. In a Neural Network, Each node of these hidden layers has its own _______ which it executes on the data received from the input layer.
a. Machine Learning Methods
b. Machine Learning Approach
c. Machine Learning Algorithm 
d. All of the above

56. The last hidden layer passes the final processed data to the _________ which then gives it to the user as the final output.
a. Output Layer 
b. Input Layer
c. Hidden Layer
d. All of the above

57. A secret AI hiring tool was being developed by Amazon. The machine learning experts discovered a significant issue: their new recruiting engine disliked women. The system has already learned that male candidates were preferred. The resumes with “women” on them were punished. As a result, the tool failed. This is an example of___________.
a. Data Privacy
b. AI Access
c. AI Bias 
d. Data Exploration

58. Which of the following datasets can have a particular structure or pattern?
a. Semi Structure
b. Structured 
c. Unstructured
d. Fully Structured

59. Which of the following models the connections or data patterns that the developer defined?
a. Rule Base Approach 
b. Learning Based Approach
c. Knowledge Based Approach
d. Decision Based Approach

60. It gives us a suitable framework that can help us get closer to the objective of our AI project.
a. 4Ws Canvas
b. AI Project Cycle 
c. Project Model
d. AI Models

61. The computer is trained using an enormous quantity of data in _________, which helps it train itself based on the data.
a. Supervised learning
b. Deep learning 
c. Classification
d. Unsupervised learning

62. Choose one of the following statements regarding the unsupervised learning-based model that is false.
a. We can provide a very large data set.
b. The algorithm itself analyzes the data set and determines relationships within that data.
c. The labeled data is fed with some rules by the developers. 
d. lets us make predictions and improve the algorithms on its own.

63. _______ is a method of dividing a node into two or more sub-nodes.
a. Data Features
b. Splitting 
c. 4Ws Canvas
d. Web Scraping

64. Select the Decision Tree nodes from the list below.
a. Decision nodes
b. End nodes
c. Chance nodes
d. All of the above 

65. Which one of the following is not a modelling approach?
a. Root
b. Terminal 
c. Interior
d. Parent

66. Which one of the following approaches is not taken into account while modelling:
a. Rule-based approach
b. Learning-based approach
c. Knowledge-based approach 
d. All of these

67. ________ is an example of a business problem when we categorize an observation as “Safe,” “AtRisk,” or “Unsafe.”
a. Classification 
b. Clustering
c. Regression
d. Dimensionality Reduction

68. Data exploration is possible with the use of ___________.
a. Problem Scoping
b. Data Visualization 
c. Data Features
d. Web Scraping

69. Techniques for data visualization are used to ______________.
a. Data discovery
b. Large data evaluation in real time
c. Gaining fresh perspectives on data
d. All of the above 

70. The ___________ is the first stage of the AI project cycle.
a. Problem Scoping 
b. Data Acquisition
c. Data Exploration
d. Data Modelling

71. The ___________ is the second stage of the AI project cycle.
a. Problem Scoping
b. Data Acquisition 
c. Data Exploration
d. Data Modelling

72. The ___________ is the third stage of the AI project cycle.
a. Problem Scoping
b. Data Acquisition
c. Data Exploration 
d. Data Modelling

73. The ___________ is the fourth stage of the AI project cycle.
a. Problem Scoping
b. Data Acquisition
c. Data Exploration
d. Data Modelling 

74. The ___________ is the fifth stage of the AI project cycle.
a. Problem Scoping
b. Data Evaluation 
c. Data Exploration
d. Data Modelling

75. The data that is provided as input during data collecting is referred to as ___________.
a. Testing Data
b. Training Data 
c. Input data
d. None of the above

76. The kind of data that is being gathered during data collection is referred to as __________.
a. System Mapping
b. Web Scraping
c. 4Ws Canvas
d. Data Features 

77. Initial problem definition is the first step in the AI process, which is afterwards
a. Designing >> Brainstorming >> Building
b. Designing >> Deploying >> Brainstorming
c. Brainstorming >> Designing >> Building 
d. Designing >> Brainstorming >> Building

78. Sumit is studying the phases of an AI project. She was aware of the problem statement template, but she is now attempting to recall it. For the problem statement template, which of the following statements is true?
a. Help people in creating a single overview that includes all the important details
b. Help in looking back and analyzing the issue in the future
c. Contains fundamental information regarding the issue’s general dimensions.
d. All of the above 

79. Data was entered into the system by Vikash, who is presently receiving the results, which she will examine. The name of this result set is _______.
a. Result Set
b. Database
c. Training Data
d. Testing Data 

80. Manish work in a Nirma Constructions. He has a list of questions and inquiries that his clients can respond to with a yes or no. This approach is called ____________.
a. Surveys
b. Web scraping
c. Sensors
d. None of the above 

81. The team leader Rakesh wants to use the observational method to gather data. Which tool from the list below may be utilize for the same?
a. Website Article
b. Google Forms
c. Checklist 
d. All of these

82. What do you mean by Web Scraping?
a. Utilizing automated bots to browse the internet and collect data 
b. Gathering information from the dark web
c. Using an app or website to collect data
d. None of the above

83. Data can be directly downloaded from any website. What kinds of data are available for free download and use?
a. Someone’s property
b. Data generated by a specific group
c. Open Source Data 
d. Closed Source Data

84. Amit has gathered information. But he discovered that the material he gathered is exceedingly challenging to comprehend. given that data is always
a. Complex entity 
b. Filtered and bifurcated
c. Sophisticated structured
d. None of the above

85. When Rajesh explores data, she wants to compare the data and demonstrate certain cyclical variations. Which graph from the following can be used?
a. Bar Graph 
b. Line Graph
c. Pie Graph
d. Histogram Graph

86. Select the five phases of the AI project cycle in the proper order.
a. Data Acquisition -> Problem Scoping -> Data Exploration -> Modelling -> Evaluation
b. Evaluation -> Problem Scoping -> Data Exploration -> Data Acquisition -> Modelling
c. Problem Scoping -> Data Acquisition -> Data Exploration -> Modelling -> Evaluation 
d. Problem Scoping -> Data Exploration -> Data Acquisition -> Evaluation -> Modelling

87. In order to have a clearer view, we examine several parameters that have an impact on the problem we’re trying to address under the _______ stage of the AI Project Cycle.
a. Data Exploration
b. Evaluation
c. Modelling
d. Problem Scoping 

88. Reviewing the project or business requirements for the AI model
a. Data Exploration
b. Evaluation
c. Modelling
d. Problem Scoping 

89. What do you mean by Problem Scoping?
a. Creating an algorithm to solve a problem
b. Proper solution of a problem
c. Recognizing a problem and having a plan to address it. 
d. analyzing the trends in the collected data sets

90. How many SDGs have been officially announced by the UN?
a. 18
b. 17
c. 16
d. 15

91. People that experience the mentioned issue and would gain from the solution are referred to as ___________.
a. Key Persons
b. Stakeholders 
c. End user
d. None of the above

92. The person starting a project should be absolutely clear with ___________.
a. Problem Reasons
b. Problem Statement 
c. Problem Solutions
d. None of the above

93. Which of the information sharing about problem scoping?
a. It will increase misunderstanding among stakeholders 
b. It is a tool that ensures the issue won’t arise again
c. While adding actual value to the organization
d. The data flow is understood clearly

94. What is the Problem Statement Template, exactly?
a. Data set that was compiled to identify the essential components of a problem
b. The template summarizes each card in the 4Ws Problem Canvas 
c. The template offers the data set’s prediction.
d. None of the above

95. Which of the following 4Ws canvas problems aids in the direct or indirect analysis of those who are affected?
a. What
b. Who 
c. Why
d. Where

96. The nature of the problem is determined by which of the 4Ws of problem scoping is used.
a. What 
b. Who
c. Why
d. Where

97. The ________ helps in collecting all the important information into a single template for problem scoping.
a. Problem Taking Template
b. 4ws of problem scoping 
c. Information Template
d. Problem Statement Template

98. Which block of the 4ws problem canvas focuses on the problem’s context, circumstance, or location? ​
a. What
b. Who
c. Why
d. Where 

99. Which of the following is not a part of the problem scoping’s 4 W?
a. What
b. Who
c. Why
d. When 

100. The 4Ws canvas is related to ___________.
a. Data exploration
b. Data Acquisition
c. Modelling
d. Problem Scoping 

101. Method of data acquisition is ___________.
a. Google Cloud
b. Programing
c. Survey 
d. All of the above

102. Which of the following is not a reliable source for acquiring data?
a. System Hacking 
b. Surveys
c. Website
d. None of the above

Employability skills Class 10 Notes

• Unit 1- Communication Skills Class 10 Notes
• Unit 2- Self-Management Skills Class 10 Notes
• Unit 3- Basic ICT Skills Class 10 Notes
• Unit 4- Entrepreneurial Skills Class 10 Notes
• Unit 5- Green Skills Class 10 Notes

Employability skills Class 10 MCQ

• Unit 1- Communication Skills Class 10 MCQ
• Unit 2- Self-Management Skills Class 10 MCQ
• Unit 3- Basic ICT Skills Class 10 MCQ
• Unit 4- Entrepreneurial Skills Class 10 MCQ
• Unit 5- Green Skills Class 10 MCQ

Employability skills Class 10 Questions and Answers

• Unit 1- Communication Skills Class 10 Questions and Answers
• Unit 2- Self-Management Skills Class 10 Questions and Answers
• Unit 3- Basic ICT Skills Class 10 Questions and Answers
• Unit 4- Entrepreneurial Skills Class 10 Questions and Answers
• Unit 5- Green Skills Class 10 Questions and Answers

Artificial Intelligence Class 10 Notes

• Unit 1 – Introduction to Artificial Intelligence Class 10 Notes
• Unit 2 – AI Project Cycle Class 10 Notes
• Unit 3 – Natural Language Processing Class 10 Notes
• Unit 4 – Evaluation Class 10 Notes
• Advanced Python Class 10 Notes
• Computer Vision Class 10 Notes

Artificial Intelligence Class 10 MCQ

• Unit 1 – Introduction to Artificial Intelligence Class 10 MCQ
• Unit 2 – AI Project Cycle Class 10 MCQ
• Unit 3 – Natural Language Processing Class 10 MCQ
• Unit 4 – Evaluation Class 10 MCQ

Artificial Intelligence Class 10 Questions and Answers

• Unit 1 – Introduction to Artificial Intelligence Class 10 Questions and Answers
• Unit 2 – AI Project Cycle Class 10 Questions and Answers
• Unit 3 – Natural Language Processing Class 10 Questions and Answers
• Unit 4 – Evaluation Class 10 Questions and Answers