Solution of class 12 Artificial Intelligence 2024 Paper Code 843
CBSE | DEPARTMENT OF SKILL EDUCATION
ARTIFICIAL INTELLIGENCE (SUBJECT CODE -843)
CBSE Board Question Paper with Solution for Class XII (Session 2023-2024)
Max. Time: 2 Hours Max. Marks: 50
General Instructions:
- Please read the instructions carefully.
- This Question Paper consists of 21 questions in two sections: Section A & Section B.
- Section A has Objective type questions whereas Section B contains Subjective type questions.
- Out of the given (5 + 16 =) 21 questions, a candidate has to answer (5 + 10 =) 15 questions in the allotted (maximum) time of 2 hours.
- All questions of a particular section must be attempted in the correct order.
- SECTION A – OBJECTIVE TYPE QUESTIONS (24 MARKS):
i. This section has 05 questions.
ii. Marks allotted are mentioned against each question/part.
iii. There is no negative marking.
iv. Do as per the instructions given. - SECTION B – SUBJECTIVE TYPE QUESTIONS (26 MARKS):i. This section has 16 questions.
ii. A candidate has to do 10 questions.
iii. Do as per the instructions given.
iv. Marks allotted are mentioned against each question/part.
Section-A (Objective Type Questions – 24 marks)
Q 1. Answer any 4 out of the given 6 questions on Employability Skills (1 x 4 = 4 marks)
| Q. No | Question | Answer |
|---|---|---|
| i | __________ is a form of communication that allows students to put their feelings and ideas on paper, to organize their knowledge and beliefs into, convincing arguments, and to convey meaning through well-constructed text. (a) Active Listening (b) Writing (c) Absolute Phrase (d) Speeches | b |
| ii | The term OCPD stands for ______. (a) Obsessive Compulsive Personality Disorder (b) Operational Compulsive Personality Disorder (c) Obsessive Compulsive Personality Defect (d) Organised Compulsive Professional Disorder | a |
| iii | Identify the incorrect statement from the following : (a) Motivation and positive thinking can help us overcome fears and take up new challenges. (b) Motivation and positive thinking can help us in ignoring our duties. (c) An individual’s motivation may come from within or be inspired by others or events. (d) Directing behaviour towards certain motive or goal is the essence of motivation. | b |
| iv | Which of the following statements is NOT true for spreadsheet? (a) A workbook has one or more worksheets. (b) Large volumes of data can be easily handled and manipulated. (c) Data cannot be easily represented in pictorial form like graphs or charts. (d) Built-in functions make calculations easier, faster and more accurate. | c |
| v | Which of the following is one of the barriers that an entrepreneur may face ? (a) Self-confidence (b) Availability of monetary resources on time (c) Unavailability of monetary resources on time. (d) Availability of skilled labour/staff. | b |
| vi | A ____________ is defined as one that helps bring about and maintain transition to environmentally sustainable forms of production and consumption. (a) Blue collar job (b) White collar job (¢) Yellow job (d) Green job. | c |
Q 2. Answer any 5 out of the given 6 questions (1 x 5 = 5 marks)
| Q. No | Question | Answer |
|---|---|---|
| i | During Train-Test split evaluation, we usually split the data around ____________ between testing and training stages. (a) 90% —10% (b) 20% — 80% (c) 100%—0% (d) 0% – 100% | b |
| ii | With reference to Data storytelling, complete the given statement : “Data can be persuasive, but are much more.” (a) Machines (b) Projects (c) Stories (d) Humans | c |
| iii | _____________ provides a useful abstract model for thinking about time series generally and for better understanding problems during time series analysis and forecasting. (a) Decomposition (b) Modelling (c) Stages (d) Building | a |
| iv | The first fundamental step when starting an Al initiative is ____________. (a) Evaluation (b) Testing (c) Deployment (d) Scoping, | d |
| v | Which of the following is not one of the steps of an Al project life cycle? (a) Problem definition (b) Understanding the problem (c) Data delivery (d) Data gathering | c |
| vi | Which of the following does not come under open languages category, used for Al development platforms? (a) Linux (b) Python (c) R (d) Scala | a |
Q 3. Answer any 5 out of the given 6 questions (1 x 5 = 5 marks)
| Q. No | Question | Answer |
|---|---|---|
| i | _______ is the last step in the Al project life cycle. (a) Problem definition (b) Data gathering (¢) Deployment (d) Evaluation | c |
| ii | Identify the given element that makes a compelling data story and choose its correct name from the following options: (a) Graphs (b) Numbers (c) Story (d) Data | d |
| iii | In ____________ phase, it’s crucial to precisely define the strategic business objectives and desired outcomes of the project. (a) Design (b) Deployment (c) Testing (d) Requirement Analysis | d |
| iv | Assertion (A): With reference to Data storytelling, narrative is the way we simplify and make sense of a complex world. Reason (R): Narrative explains what is going on within the dataset. Select the appropriate option for the statements given above: (a) Both (A) and (R) are true and (R) is the correct explanation of (A). (b) Both () and (R) are true and (R is not the correct explanation of (A). (c) (A) is true but (R) is false. (d) (A) is false but (R) is true. | a |
| v | Al is perhaps the most transformative technology available today, At a high level, every Al project follows total _________________ steps. (a) Six (b) Seven (c) Eight (d) Infinite | a |
| vi | During step-3 of Al model life cycle, should include all relevant subsets of training data, (a) Relevant Data (b) Deployment (c) Test data (d) Scoping | b |
Q 4. Answer any 5 out of the given 6 questions (1 x 5 = 5 marks)
| Q. No | Question | Answer |
|---|---|---|
| i | Match the following:  (a) 1-D, 2-A, 3-B, 4-C (b) 1-D, 2-C, 3-B, 4-A (c) 1-B, 2-A, 8-D, 4-C (d) 1-C, 2-B, 3-A,4-D | b |
| ii | Stories that incorporate ______ and analytics are more convincing than those based entirely on anecdotes or personal experience. (a) Suspense (b) Humour (c) Data (d) Energy | c |
| iii | During modelling approach of Capstone project, the data scientist will use a _____ get for predictive modelling, (a) Training (b) Testing (c) Valuable (d) Known | a |
| iv | As Data Storytelling is a structured approach for communicating insights drawn from data, and invariably involves a combination of key elements. When the ______ is accompanied with data, it helps to explain the audience what’s happening in the data and why a particular insight has been generated. (a) Data (b) Visuals (c) Narrative (d) Story | c |
| v | With reference to Al Model Life Cycle, which of the following is true for Building the Model? (a) This is arguably the most important part of your Al project. (b) Phrase that characterizes this project stage: “garbage in, garbage out”. (c) This stage involves the planning and motivational aspects of your project. (d) It is essentially an iterative process comprising all the steps relevant to building the Al or machine learning model. | d |
| vi | RMSE stands for ______. (a) Root Median Squared Error (b) Radian Mean Squared Error (c) Root Mean Search Error (d) Root Mean Squared Error | d |
Q 5. Answer any 5 out of the given 6 questions (1 x 5 = 5 marks)
| Q No | Question | Answer |
|---|---|---|
| i | Good stories don’t just emerge from data itself; they need to be unravelled from relationships. (a) Data (b) Numbers (c) Charts (d) Computer | a |
| ii | The train-test procedure is appropriate when there is a sufficiently data sets available. (a) Comparative (b) Large (c) Small (d) Equal | b |
| iii | During the third step of AI Model Life Cycle, the volume of test data can be large, which presents _____ (a) Complexities (b) Accuracy (c) Efficiency (d) Redundancy | a |
| iv | In ____, we run our modelling process on different subsets of the data to get multiple measures of model quality. (a) Train-Test Split (b) Regression (c) Cross-validation (d) Machine learning | c |
| v | The machine learning life cycle is the _____ process that AI or machine learning project follow. (a) Irreversible (b) Cyclic (c) One-time (d) Static | b |
| vi | Data Modelling focuses on developing models that are either descriptive or ______. (a) Inclusive (b) Predictive (c) Selective (d) Reactive | b |
Section-B (Subjective Type Questions – 26 marks)
Answer any 3 out of the given 5 questions on Employability Skills (2 x 3 = 6 marks)
Answer each question in 20 – 30 words.
| Q6 | Differentiate between ‘sentence’ and ‘phrase’ with the help of suitable example. | 2 |
| Ans | Sentences: Grammatically complete: Contain a subject and a verb (predicate). Convey a complete thought: Express a full idea on their own. Examples: “The sun is shining.” “I love learning.” Phrases: Grammatically incomplete: May lack a subject or a verb. Don’t convey a complete thought: Function as units within a sentence. Examples: “In the morning” (missing verb), “learning a new skill” (missing subject). | |
| Q7 | Briefly explain the following terms: (a) Personality (b) Personality disorders | 2 |
| Ans | (a) Personality: The enduring patterns of thoughts, feelings, and behaviors that characterize an individual. It reflects how someone typically behaves and interacts with the world. (b) Personality disorders: Inflexible and nonadaptive patterns of thinking, feeling, and behaving that deviate significantly from cultural expectations and cause distress or impairment in functioning. | |
| Q8 | Mr. Chowdhary wants to explain the working of a product to his clients. To make an impact on their audience, either he can use homemade charts or make a digital presentation using a computer and presentation software. Which out of the two options is more advantageous and why? | 2 |
| Ans | A Digital Presentation is generally more advantageous: (i) Professionalism and Polish: Creates a more professional and polished impression compared to homemade charts. (ii) Engagement and clarity: Allow for multimedia elements (e.g., videos, animations) to enhance engagement and clarify complex concepts. (iii) Ease of sharing and updating: Easier to share with clients electronically and update as needed, compared to physical charts. | |
| Q9 | What do you mean by interpersonal skills? Why is it important for an entrepreneur to possess it? Briefly discuss. | 2 |
| Ans | Interpersonal skills are the ability to effectively communicate, build relationships, and collaborate with others. These skills are crucial for entrepreneurs because they need to: (i) Communicate their vision and ideas persuasively to investors, partners, and customers. (ii) Build strong relationships with stakeholders to secure funding, collaborate on projects, and foster customer loyalty. (iii) Navigate complex situations and resolve conflicts effectively. | |
| Q10 | Mention any four advantages of Green jobs. | 2 |
| Ans | (i) Environmental benefits: Contribute to sustainability by reducing pollution, conserving resources, and mitigating climate change. (ii) Economic growth: Create new job opportunities in growing sectors like renewable energy and resource efficiency. (iii) Improved public health: Reduce air and water pollution, leading to healthier communities. (iv) Innovation and development: Promote the development and adoption of clean technologies and sustainable practices. |
Answer any 4 out of the given 6 questions in 20 – 30 words each (2 x 4 = 8 marks)
| Q11 | What is a training set? | 2 |
| Ans | A training set is a subset of data used to “train” a machine learning model. It’s comprised of input-output pairs used for algorithm learning and parameter adjustment. This data helps the model learn patterns and relationships within the data, allowing it to make predictions or perform specific tasks on new, unseen data. | |
| Q12 | Name the two categories of loss functions. | 2 |
| Ans | Regression Loss Functions: Used when the target variable is continuous, such as predicting house prices or stock prices. Examples include Mean Squared Error (MSE) and Mean Absolute Error (MAE). Classification Loss Functions: Used when the target variable is categorical, meaning it belongs to one of a finite number of discrete classes, such as classifying emails as spam or not spam. Examples include Cross-Entropy and Hinge Loss. | |
| Q13 | “Stories create engaging expressions that transport the audience to another space and time”. Justify this statement. | 2 |
| Ans | Train-Test Split: This involves dividing the data into two sets: a training set used to train the model and a testing set used to evaluate its performance on unseen data. Cross-validation: This involves dividing the data into multiple folds and repeatedly training the model on one fold while evaluating on the remaining folds. This provides a more robust estimate of the model’s generalizability. | |
| Q14 | What is a Capstone project? Give any two examples. | 2 |
| Ans | Stories tap into our imagination and emotions, allowing us to visualize ourselves in different settings and situations. This creates a powerful connection to the narrative, making it feel like we are experiencing the events firsthand, regardless of space or time. | |
| Q15 | Name the two techniques that can be used to validate AI model quality. | 2 |
| Ans | Train-Test Split: This involves dividing the data into two sets: a training set used to train the model and a testing set used to evaluate its performance on unseen data. Cross-validation: This involves dividing the data into multiple folds and repeatedly training the model on one-fold while evaluating on the remaining folds. This provides a more robust estimate of the model’s generalizability. | |
| Q16 | Name any two open frameworks and two development tools that can be used to build an AI model. | 2 |
| Ans | Open Frameworks: (i) TensorFlow: A popular framework by Google, renowned for flexibility and scalability. (ii) PyTorch: A Python-based framework known for its user-friendliness and ease of debugging. (iii) Keras: A high-level API often used with TensorFlow or other frameworks, simplifying model building. Development Tools: (i) Jupyter Notebook: A web-based interactive environment for code, visualizations, and documentation. (ii) Visual Studio Code: A popular code editor with extensive functionality and AI extensions. (iii) Git: A version control system for tracking changes and collaborating on code development. |
Answer any 3 out of the given 5 questions in 50– 80 words each (4 x 3 = 12 marks)
| Q17 | List any four importance of Data Storytelling. | 4 |
| (i) Engages audience: Stories make data more engaging and memorable, fostering deeper understanding and connection with the information. (ii) Improves communication and persuasion: By weaving data into a narrative, complex insights become easier to grasp and communicate, fostering persuasion and action. (iii) Connects with emotions: Stories tap into our emotions, making data resonate on a deeper level and leaving a lasting impression. (iv) Enhances decision-making: Data storytelling helps people understand complex information and context, enabling informed and data-driven decisions. | ||
| Q18 | What is Design Thinking? List its main stages. | 4 |
| Design Thinking is an iterative, human-centered approach to problem-solving. It focuses on understanding users’ needs, exploring solutions, and iteratively refining them based on feedback. The main stages of Design Thinking are: (i) Empathize: Understand the problem from the user’s perspective. (ii) Define: Clearly define the problem based on user needs and observations. (iii) Ideate: Brainstorm and generate creative solutions to the problem. (iv) Prototype: Develop quick, tangible representations of potential solutions. (v) Test: Gather user feedback on the prototypes to refine and improve the solution. | ||
| Q19 | Explain the “Design/Building the Model” step of the AI Model lifecycle in detail. | 4 |
| Once the relevant projects have been selected and properly scoped, the next step of the machine learning lifecycle is the Design or Build phase, which can take from a few days to multiple months, depending on the nature of the project. The Design phase is essentially an iterative process comprising all the steps relevant to building the AI or machine learning model: 1. data acquisition, 2. exploration, 3. preparation, 4. cleaning, 5. feature engineering, 6. testing and running a set of models to try to predict behaviors or discover insights in the data. During this phase, we need to evaluate the various AI development platforms, e.g.: 1. Open languages — Python is the most popular, with R and Scala also in the mix. 2. Open frameworks — Scikit-learn, XGBoost, TensorFlow, etc. 3. Approaches and techniques — Classic ML techniques from regression all the way to state-of-theart GANs and RL 4. Productivity-enhancing capabilities — Visual modelling, AutoAI to help with feature engineering, algorithm selection and hyperparameter optimization 5. Development tools — DataRobot, H2O, Watson Studio, Azure ML Studio, Sagemaker, Anaconda, etc. | ||
| Q20 | Expand and explain the term MSE. Give the mathematical formula to calculate MSE. Why use MSE? Briefly discuss. | 4 |
| Mean Square Error (MSE) is the most commonly used regression loss function. MSE is the sum of squared distances between our target variable and predicted values. Mathematical Formula to calculate MSE:  Why use MSE? MSE is sensitive towards outliers and given several examples with the same input feature values, the optimal prediction will be their mean target value. This should be compared with the Mean Absolute Error, where the optimal prediction is the median. MSE is thus good to use if you believe that your target data, conditioned on the input, is normally distributed around a mean value, and when it’s important to penalize outliers extra much. | ||
| Q21 | (a) Why Storytelling is so powerful and cross-cultural? Explain. | 4 |
| (a) Storytelling is a powerful and cross-cultural tool for communication and understanding for several reasons: Universality of Human Experience: At their core, stories tap into the fundamental experiences that make us human: love, loss, triumph, conflict, and the search for meaning. These themes resonate across cultures even when specific details change. Emotional Connection: Stories work by engaging our emotions, and fostering empathy for characters and their situations. This emotional connection transcends cultural barriers, allowing the audience to relate to an experience even if it’s not directly theirs. Pattern Recognition: The human brain is wired to understand the world through stories. We look for patterns, causality, and narratives to make sense of complex information. Stories offer this structure, making concepts easier to understand and memorize. Collective Memory and Identity: Stories often reflect cultural values, beliefs, and history. By sharing stories, communities across the globe preserve their traditions, reinforce their shared identity, and pass down important knowledge to future generations. | ||
| Q21. | (b) Which of the following is a better data story? Give reasons.   | |
| Option (b) Second (Image 2) data story is better because it has more observations related to the data. It will help to create a more engaging and captivating story. |
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