Class 10th 417 Important Question Bank for Board
IMPORTANT QUESTION
Employability Skills & AI – Questions with Solutions
Q1. Employability Skills
i. Pranjali wakes up early, attends classes, completes homework without being told. This is an example of:
ii. Which of the following is a valid Notepad file extension?
iii. Ravi remains calm while customer shouts. He is:
iv. Statement 1: A realistic goal has no timeline. Statement 2: Breaking big goals into smaller parts makes them achievable.
v. Rohit waves his hand while saying goodbye. This is:
vi. Aim of Sustainable Development:
Q2. AI Basics
i. Chatbots belong to which AI domain?
ii. Discriminatory results due to developer assumptions are called:
iii. Which layer performs processing in neural networks?
iv. Neural networks have layers of neurons; the human brain also has neurons.
v. Constantly following someone is called:
vi. Combined textual data from multiple documents is called:
Q3. AI Concepts
i. Which are NOT AI?
ii. AI Project Cycle is a:
iii. Data Science involves:
iv. Ratio of true negatives to all actual negatives:
v. Simple FAQ chatbot:
vi. Percentage of correct predictions:
Q4. AI & Evaluation
i. Identify algorithm from grouping graph:
ii. F1 score depends on precision and recall; F1=0 means 100% accuracy.
iii. Spam filtering is:
iv. Problem scoping element identifying affected people:
v. Converting text to common case is a step in normalization.
vi. Extracting emotions from text is called:
Q5
i. Number of tokens in paragraph:
36
ii. Recall does not depend on True Negative.
True
iii. Pixel value in grayscale represents:
iv. Chatbot answering Economics doubts domain:
v. Important for Good AI Machine:
vi. Problem scoping involves:
Solutions - Employability Skills & AI MCQs
Section 1
(i) Which self-management skill is visible?
(ii) Software that manages hardware and software resources:
(iii) Barrier when technical jargon is used:
(iv) Sustainable development aims at:
(v) Entrepreneurship mindset example:
(vi) Permanent delete shortcut:
Section 2
(i) First stage of AI Project Cycle:
(ii) Face unlock application:
(iii) Dividing corpus into words:
(iv) Data used to check model performance:
(v) AI domain dealing with human language:
(vi) Final result layer in Neural Network:
Section 3
(i) 4Ws: Who, What, Where and:
(ii) NOT part of Data Exploration:
(iii) Set of all unique words:
(iv) Evaluation checks:
(v) Stemming & Lemmatization belong to:
(vi) Example of Narrow AI:
Section 4
(i) Reducing word to dictionary base form:
(ii) F1 Score is harmonic mean of:
(iii) Prediction Yes & Reality Yes:
(iv) Best graph for relationship:
(v) Limitation of Rule-based NLP:
(vi) Small dots in image:
Section 5
(i) Labeled data learning:
(ii) Difference between actual & predicted:
(iii) Full form of TF-IDF:
(iv) Identify location of multiple objects:
(v) Confusion Matrix evaluates:
(vi) 'Where' block focuses on:
Q6. Ways to Overcome Barriers to Effective Communication
1. Practice Active Listening:
Give full attention to the speaker without interrupting. Maintain eye contact,
nod to show understanding, and ask relevant questions if clarification is needed.
Active listening reduces misunderstandings and ensures that the message is clearly received.
2. Use Clear and Simple Language:
Avoid complicated words, technical terms, or vague statements.
Communicate your ideas in a simple, direct, and organized manner.
Clear language minimizes confusion and helps the listener understand the message accurately.
Q7. Quality Demonstrated by Raghu
What is Raghu doing?
Raghu is practicing time management and self-discipline. By planning and scheduling
his daily activities in advance, he ensures that his tasks are completed in an organized
and timely manner.
Elaboration on the Quality:
The quality seen in Raghu is effective time management. This habit helps in setting priorities,
avoiding last-minute stress, and improving productivity. When a person schedules tasks,
they are more likely to stay focused and use their time efficiently. It also builds a sense
of responsibility and control over daily activities.
This is a valuable quality that I can adopt in my own life. By planning my day, I can balance studies, personal activities, and rest properly. It will help me meet deadlines, reduce distractions, and achieve my goals more effectively.
Q8. Various Threats to a Computer and Its Data
Computers and digital data are exposed to several types of threats that can damage hardware, corrupt files, steal sensitive information, or disrupt normal operations. Some of the major threats are explained below:
- 1. Viruses: Malicious programs that attach themselves to files or software. They spread from one system to another and can damage or delete data.
- 2. Malware: A general term for harmful software such as worms, trojans, and spyware. Malware can steal personal information, monitor activities, or slow down the system.
- 3. Phishing: Fraudulent attempts to obtain sensitive information like passwords or bank details through fake emails, websites, or messages.
- 4. Ransomware: A type of malicious software that locks or encrypts files and demands payment to restore access to the data.
- 5. Hacking: Unauthorized access to a computer system or network with the intention of stealing, altering, or destroying information.
- 6. Data Theft: Sensitive data such as financial records, passwords, and personal details may be stolen if proper security measures are not in place.
- 7. Physical Damage: Hardware can be damaged due to power surges, overheating, water exposure, or mishandling, leading to data loss.
- 8. Weak Passwords: Simple or commonly used passwords make it easier for attackers to gain access to accounts and systems.
To protect computers and data, it is important to use antivirus software, strong passwords, regular backups, secure networks, and updated systems.
Q9. Two Qualities of Successful Entrepreneurs
1. Risk-Taking Ability:
Successful entrepreneurs are willing to take calculated risks. They understand that starting and running a business involves uncertainty. Instead of fearing failure, they evaluate possible outcomes, plan carefully, and make informed decisions. This ability to step out of their comfort zone helps them explore new opportunities and grow their ventures.
2. Leadership Skills:
A strong entrepreneur knows how to guide and inspire a team. Leadership involves clear communication, decision-making, and motivating others toward a common goal. Effective leaders build trust, encourage teamwork, and handle challenges confidently. This quality ensures that the business moves forward smoothly even during difficult situations.
These qualities help entrepreneurs overcome obstacles, adapt to change, and achieve long-term success in their business journey.
What are the core skills required by a person who wants to contribute towards environment?
A person who wants to actively contribute towards environmental protection should develop certain essential skills. These skills help in promoting sustainable practices and responsible use of natural resources.
- Environmental Awareness: Understanding environmental issues such as pollution, climate change, waste management, and conservation of resources.
- Critical Thinking: The ability to analyze environmental problems and identify effective and practical solutions.
- Responsibility: Taking personal accountability for actions like reducing waste, saving energy, and conserving water.
- Problem-Solving Skills: Developing innovative approaches to handle environmental challenges in daily life and community activities.
- Teamwork: Collaborating with others in environmental campaigns, cleanliness drives, and awareness programs.
- Communication Skills: Spreading awareness and encouraging others to adopt eco-friendly habits.
- Adaptability: Being open to changing habits and adopting sustainable alternatives for long-term environmental benefits.
By developing these core skills, individuals can actively participate in protecting the environment and supporting sustainable development for present and future generations.
What is AI Access?
AI Access refers to the ability of individuals, organizations, or systems to use Artificial Intelligence technologies, tools, and services. It means having the required resources such as software platforms, hardware devices, internet connectivity, and technical knowledge to interact with AI systems.
AI access can be provided through various mediums such as mobile applications, web platforms, cloud services, APIs, or integrated smart devices. When people have proper access to AI, they can use it for learning, business, healthcare, communication, research, and automation purposes.
Ensuring equal AI access is important because it helps reduce the digital divide and allows more people to benefit from intelligent technologies. It also promotes innovation, productivity, and inclusive development in society.
Problem Statement Template and Its Significance
What is a Problem Statement Template?
A problem statement template is a structured format used to clearly describe an issue that needs to be solved. It helps in defining the problem in a precise, organized, and measurable manner. Instead of describing a problem in a vague way, the template guides the user to include important elements such as the context, affected stakeholders, existing challenges, and the desired outcome.
A typical problem statement template may include:
- Who is affected by the problem?
- What exactly is the issue?
- Where does the problem occur?
- Why is it important to solve the problem?
- How can the situation be improved?
Significance of a Problem Statement Template
- Clarity: It clearly defines the problem, avoiding confusion or misunderstanding.
- Focus: It helps teams concentrate on the real issue rather than unrelated matters.
- Better Planning: A well-defined problem makes it easier to design appropriate solutions.
- Stakeholder Understanding: It ensures everyone involved understands the scope and impact of the issue.
- Improved Decision-Making: Clear identification of the problem supports effective and logical decisions.
In summary, a problem statement template provides structure and direction, making it easier to analyze challenges and develop meaningful solutions.
Q13. What is Machine Learning?
Machine Learning is a branch of Artificial Intelligence that enables computers to learn from data and improve their performance without being explicitly programmed for every task. Instead of following fixed instructions, a machine learning system analyzes patterns in data and makes predictions or decisions based on that analysis.
In machine learning, algorithms are trained using data. The system identifies relationships within the data and adjusts its internal parameters to minimize errors. Over time, the model becomes more accurate as it gains more experience or is exposed to additional data.
Machine learning is widely used in applications such as spam detection, recommendation systems, speech recognition, image classification, and predictive analytics.
In simple terms, machine learning allows computers to learn from experience and become smarter with practice.
Q14. Computer Vision and Its Primary Goal
Computer Vision is a field of Artificial Intelligence that enables computers and machines to interpret and understand visual information from the world, such as images and videos. It allows systems to identify objects, recognize patterns, detect movements, and analyze visual data in a way similar to how humans use their eyes and brain.
Computer Vision works by using algorithms and models, especially deep learning techniques, to process digital images and extract meaningful information from them. The system first converts images into numerical data and then analyzes this data to make decisions or classifications.
The primary goal of Computer Vision is to enable machines to automatically analyze and interpret visual data accurately and efficiently. It aims to reduce human effort in tasks such as object detection, facial recognition, medical image analysis, traffic monitoring, and autonomous driving.
In simple terms, Computer Vision helps machines "see" and understand images and videos to perform intelligent actions.
Q15. Need of Text Normalization in NLP
Text Normalization is an important preprocessing step in Natural Language Processing (NLP). It involves converting text into a standard and consistent format so that machines can analyze and understand it more effectively.
In real-world data, text often contains variations such as uppercase and lowercase letters, punctuation marks, extra spaces, abbreviations, slang words, and spelling differences. These inconsistencies can create confusion for machine learning models and reduce accuracy. Text normalization removes or standardizes such variations to make the data uniform.
The need for text normalization includes:
- Improving model accuracy by reducing unnecessary variations in words.
- Making data consistent for better comparison and analysis.
- Reducing the size of vocabulary by converting similar words into a common form.
- Helping algorithms process text efficiently and faster.
Common text normalization techniques include converting text to lowercase, removing punctuation, eliminating stop words, and applying stemming or lemmatization.
In summary, text normalization ensures that textual data is clean, consistent, and ready for effective analysis in NLP applications.
Q16. Definition of Confusion Matrix
A Confusion Matrix is a performance evaluation tool used in classification models. It is a table that compares the actual values (real outcomes) with the predicted values generated by a machine learning model. This matrix helps in understanding how well the model is performing by showing correct and incorrect predictions.
In binary classification, a confusion matrix consists of four components:
- True Positive (TP): The model correctly predicts a positive outcome.
- True Negative (TN): The model correctly predicts a negative outcome.
- False Positive (FP): The model incorrectly predicts a positive outcome.
- False Negative (FN): The model incorrectly predicts a negative outcome.
These values are arranged in a tabular form as shown below:
| Actual \ Predicted | Positive | Negative |
|---|---|---|
| Positive | True Positive (TP) | False Negative (FN) |
| Negative | False Positive (FP) | True Negative (TN) |
The confusion matrix is important because it allows calculation of performance metrics such as accuracy, precision, recall, and F1-score. It provides a deeper understanding of model behavior beyond simple accuracy.
Q17. AI Model Prediction Analysis
The AI model predicts whether a customer will purchase electronic gadgets (YES/NO). Based on the given data, the confusion matrix can be interpreted as follows:
| Reality \ Prediction | YES | NO |
|---|---|---|
| YES | 10 | 25 |
| NO | 60 | 5 |
Step 1: Identify Values
- True Positive (TP) = 10
- False Negative (FN) = 25
- False Positive (FP) = 60
- True Negative (TN) = 5
Step 2: Calculate Evaluation Metrics
Total Observations = 10 + 25 + 60 + 5 = 100
Accuracy = (TP + TN) / Total = (10 + 5) / 100 = 15 / 100 = 15%
Precision = TP / (TP + FP) = 10 / (10 + 60) = 10 / 70 ≈ 14.29%
Recall = TP / (TP + FN) = 10 / (10 + 25) = 10 / 35 ≈ 28.57%
Conclusion
The model’s accuracy is very low (15%), which indicates poor performance. The high number of false positives (60) shows that the model incorrectly predicts many customers as buyers when they actually do not purchase. This model requires further improvement and better training data to enhance performance.
Q18. Text Normalization and Its Steps
Definition of Text Normalization
Text Normalization is a preprocessing technique used in Natural Language Processing (NLP) to convert raw text into a clean, consistent, and standardized format. Since real-world text data often contains variations such as uppercase letters, punctuation marks, abbreviations, and spelling differences, normalization helps reduce these inconsistencies so that machines can process text efficiently.
Steps Involved in Text Normalization
- 1. Converting to Lowercase: All text is converted into lowercase to avoid treating words like "AI" and "ai" as different terms.
- 2. Removing Punctuation: Symbols such as commas, full stops, question marks, and special characters are removed if they are not required for analysis.
- 3. Removing Extra Spaces: Unnecessary spaces between words are eliminated to maintain uniform formatting.
- 4. Tokenization: The text is broken down into smaller units called tokens (words or phrases).
- 5. Removing Stop Words: Common words such as "is", "the", "and", etc., are removed as they usually do not add significant meaning to the analysis.
- 6. Stemming: Words are reduced to their base or root form (e.g., "running" becomes "run").
- 7. Lemmatization: Words are converted into their meaningful base form using vocabulary and grammar rules (e.g., "better" becomes "good").
Conclusion
Text normalization ensures that textual data is structured, consistent, and ready for machine learning models. By cleaning and standardizing the text, it improves model accuracy, reduces vocabulary size, and enhances overall performance in NLP tasks.
Q19. Data Exploration Stage
Meaning of Data Exploration
The Data Exploration stage is an important phase in the AI Project Cycle and data science process. In this stage, the collected data is carefully examined to understand its structure, patterns, relationships, and quality. The main goal is to gain insights from the data before building a model.
Purpose of Data Exploration
- To understand the type and format of data (numerical, categorical, etc.).
- To identify missing values or incorrect data entries.
- To detect patterns, trends, and relationships between variables.
- To find outliers or unusual observations.
- To prepare the data for further processing and modeling.
Activities Involved
- Data Visualization: Using charts and graphs such as bar charts, pie charts, and histograms to understand patterns visually.
- Statistical Analysis: Calculating measures like mean, median, mode, and standard deviation to summarize the dataset.
- Data Cleaning: Handling missing values, removing duplicates, and correcting errors.
- Feature Analysis: Understanding which variables are important for solving the problem.
Conclusion
The Data Exploration stage helps in understanding the dataset thoroughly before applying machine learning techniques. It improves decision-making, enhances model performance, and reduces the chances of errors during later stages of the project.
Q20. Domains of Artificial Intelligence
Artificial Intelligence (AI) is divided into different domains based on the type of tasks machines are designed to perform. These domains focus on enabling machines to simulate human abilities such as understanding language, recognizing images, and analyzing data.
- 1. Data Science:
This domain focuses on extracting meaningful insights from structured and unstructured data. It involves data analysis, pattern recognition, and predictive modeling to support decision-making. - 2. Natural Language Processing (NLP):
NLP enables machines to understand, interpret, and respond to human language. Applications include chatbots, translation systems, speech recognition, and sentiment analysis. - 3. Computer Vision:
Computer Vision allows machines to interpret and analyze visual data such as images and videos. It is used in facial recognition, object detection, medical imaging, and self-driving cars.
These domains work together to create intelligent systems that can perceive, understand, and respond to the world in a meaningful way.
Q21. Rule-Based AI Modelling Approach
Meaning of Rule-Based AI
Rule-based AI is a modelling approach in which the behavior of the system is controlled by a predefined set of rules created by a developer. These rules are written in the form of "if-then" statements. The system follows these instructions to make decisions or provide outputs.
How It Works
In a rule-based system, the developer identifies possible conditions and defines corresponding actions. When input data is provided, the system checks it against the stored rules. If a condition matches, the system executes the related action and generates an output.
For example, in a simple chatbot:
- If the user says "Hello", then respond with "Hi! How can I help you?"
- If the user asks about timings, then provide business hours.
Characteristics of Rule-Based Approach
- Uses explicitly programmed rules.
- Does not learn from new data automatically.
- Produces predictable and consistent results.
- Works well for simple and well-defined problems.
Advantages
- Easy to design for small-scale problems.
- Transparent decision-making process.
- Requires less computational power.
Limitations
- Not flexible or adaptive.
- Cannot handle unseen situations effectively.
- Becomes complex when rules increase.
Conclusion
Rule-based AI modelling is suitable for systems where rules are clearly defined and conditions are limited. However, for complex and dynamic problems, learning-based approaches are generally more effective.
Q22. Two Qualities of a Successful Entrepreneur
1. Risk-Taking Ability:
A successful entrepreneur is willing to take calculated risks.
Starting and managing a business always involves uncertainty.
Instead of avoiding challenges, an entrepreneur carefully evaluates
possible outcomes and makes informed decisions.
This ability helps in exploring new opportunities and achieving growth.
2. Leadership Skills:
Effective entrepreneurs possess strong leadership qualities.
They guide, motivate, and inspire their team members towards achieving
common goals. Good leadership includes clear communication,
decision-making ability, and confidence in handling difficult situations.
These qualities ensure smooth functioning and long-term success of the business.
Developing these qualities enables individuals to overcome obstacles, adapt to changes, and build sustainable and successful ventures.
Q23. Difference Between Verbal and Non-Verbal Communication
| Basis | Verbal Communication | Non-Verbal Communication |
|---|---|---|
| Meaning | Communication through spoken or written words. | Communication without words, using body language and expressions. |
| Medium | Includes face-to-face conversation, phone calls, speeches, emails, and letters. | Includes gestures, facial expressions, posture, eye contact, and tone of voice. |
| Clarity | Usually direct and specific in conveying information. | Often supports or enhances verbal messages. |
| Feedback | Immediate feedback is possible during conversation. | Feedback is observed through reactions like expressions or body movements. |
| Example | Giving instructions verbally in a meeting. | Nodding the head to show agreement. |
In summary, verbal communication relies on words to convey messages, whereas non-verbal communication depends on physical cues and expressions to express thoughts and emotions.
Q24. Explain Any Two Ways to Maintain a Computer System
1. Regular Software Updates and Antivirus Protection:
Keeping the operating system and software updated ensures that the computer
has the latest security patches and performance improvements. Installing and
regularly updating antivirus software helps protect the system from viruses,
malware, and other cyber threats. This prevents data loss and keeps the system secure.
2. Regular Cleaning and Proper Handling:
Physical maintenance is equally important. Cleaning the keyboard, monitor,
and CPU prevents dust accumulation, which can cause overheating and hardware damage.
Proper handling, safe shutdown practices, and avoiding exposure to liquids or
extreme temperatures help increase the lifespan of the computer.
By following these maintenance practices, a computer system remains efficient, secure, and durable over a longer period of time.
Q25. What do you understand by "Green Economy"?
A Green Economy refers to an economic system that aims to improve human well-being and social equality while reducing environmental risks and ecological damage. It focuses on sustainable development by promoting activities that conserve natural resources, reduce pollution, and minimize carbon emissions.
In a green economy, growth is achieved through environmentally friendly practices such as renewable energy, energy efficiency, waste reduction, sustainable agriculture, and eco-friendly industries. It encourages responsible consumption and production so that present needs are met without harming the ability of future generations to meet their own needs.
In simple terms, a green economy balances economic progress with environmental protection and social welfare.