Class 12 Artificial Intelligence Previous Year Paper 2023 Compartment Solution Code 843
CBSE | DEPARTMENT OF SKILL EDUCATION
ARTIFICIAL INTELLIGENCE (SUBJECT CODE -843)
SUPPLEMENTARY/COMPARTMENT EXAMINATION 2023-24
MARKING SCHEME
Class XII
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.No. | Questions | Answer |
| Q 1. | Answer any 4 out of the given 6 questions on Employability Skills (1 x 4 = 4 marks) | |
| i. | __________ is a term used to describe a person’s ability to recognise what results are important and the steps needed to be taken to achieve them. (a) Self-reflection (b) Result orientation (c) Motivation (d) Inspiration | a |
| ii. | Which of the following personality disorders is characterised by distrust for others, including friends, family members and partners? (a) Antisocial (b) Schizoid (c) Paranoid (d) Narcissistic | c |
| iii. | ________ refers to the process of enhancing entrepreneurial skills and knowledge through structured training and institution building programmes. (a) Entrepreneur’s work culture (b) Entrepreneurship development (c) Entrepreneurship selection (d) Entrepreneur management | b |
| iv. | In a spreadsheet software, an arrangement of cells in a horizontal manner is known as: (a) Worksheet (b) Workbook (c) Column (d) Row | d |
| v. | Which of the following is not an example of a presentation software? (a) LibreOffice Impress (b) Microsoft Office – PowerPoint (c) Notepad (d) Google Slides | c |
| vi. | Individuals, who focus on developing solutions that benefit the society, are called ____________. (a) Social entrepreneurs (b) Industrial entrepreneurs (c) Agricultural entrepreneurs (d) Technical entrepreneurs | a |
| Q 2. | Answer any 5 out of the given 6 questions (1 x 5 = 5 marks) | |
| i. | Which of the following is the first step of an AI project? (a) Problem definition (b) Data gathering (c) Feature definition (d) Al model construction | a |
| ii. | Data storytelling involves a combination of ________ key elements. (a) two (b) three (c) four (d) five | b |
| iii. | A ________ set is a set of historical data in which the outcomes are already known. (a) current (b) instant (c) training (d) output | c |
| iv. | The first fundamental step, when starting an AI initiative is _________ and selecting the relevant use cases, that the AI model will be built to address. (a) scoping (b) deployment (c) thinking (d) designing | a |
| v. | The train-test procedure is appropriate when there is a sufficiently ________ dataset available. (a) small (b) moderate (c) large (d) average | c |
| vi. | In AI development, which of the following frameworks is used? (a) Python (b) Visual Basic (c) XGBoost (d) C++ | c |
| Q 3. | Answer any 5 out of the given 6 questions (1 x 5 = 5 marks) | |
| i. | Expand the term RMSE. (a) Rational Median Square Error (b) Root Median Square Estimate (c) Root Mean Squared Error (d) Root Median Sequential Estimate | c |
| ii. | 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) visuals (b) narrative (c) project (d) graphs | b |
| iii. | Which of the following is not True for Testing? (a) Data validation is important. (b) The volume of test data can be large. (c) Your testing team should test the AI and ML algorithms keeping model validation. (d) Regulatory compliance testing and security testing are not so important. | d |
| iv. | A narrative shows the audience where to look and what not to miss and also keeps the audience ________. (a) happy (b) confused (c) engaged (d) enlightened | c |
| v. | In ___________ stage, the data scientist will play around with different algorithms to ensure that the variables in play are actually required. (a) Evaluation (b) Data Modelling (c) Data requirement (d) Problem scoping | b |
| vi. | Given below are two statements, one labelled as Assertion (A) and the other labelled as Reason (R). Select the correct answer from the code given below: Assertion (A): The first fundamental step when starting an AI initiative is building the model. Reason (R): First stage of AI initiative involves the planning and motivational aspects of your project. (a) Both Assertion (A) and Reason (R) are true, and Reason (R) is the correct explanation of Assertion (A). (b) Both Assertion (A) and Reason (R) are true, but Reason (R) is not the correct explanation of Assertion (A). (c) Assertion (A) is true, but Reason (R) is false. (d) Assertion (A) is false, but Reason (R) is true. | d |
| Q 4. | Answer any 5 out of the given 6 questions (1 x 5 = 5 marks) | |
| i. | Which of the following is not a in building an AI model? (a) DataRobot (b) H2O (c) Watson Studio (d) Visual Basic | d |
| ii. | Which of the following is a key element of a data story? (a) audience (b) information (c) engage (d) narrative | d |
| iii. | If there is no _______ in the data, then the problem cannot be solved with AI technology. (a) language (b) pattern (c) logic (d) program | b |
| iv. | (iv) Data __________ is a structured approach for communicating insights drawn from data. (a) storytelling (b) representation (c) acquisition (d) exploration | a |
| v. | Which of the following are correct? (a) If the data you collect is no good, you won’t be able to build an effective AI algorithm. (b) The testing phase is essentially an iterative process. (c) Test data should not include all relevant subsets of training data. (d) Once the relevant projects have been selected and properly scoped, the next step of the machine learning life cycle is testing. | b |
| vi. | _______ functions predict a quantity, and classification functions predict a label. (a) Regression (b) Continuous (c) Algorithm (d) Dataset | a |
| Q 5. | Answer any 5 out of the given 6 questions (1 x 5 = 5 marks) | |
| i. | ______ create engaging experiences that transport the audience to another space and time. (a) Stories (b) Algorithms (c) Visualizations (d) Information | a |
| ii. | ______ is a method to find the minimum point of a function. (a) Objective function (b) Focal loss (c) Loss function (d) Gradient descent | d |
| iii. | Which of the following is the most preferred language for building an AI or machine learning model? (a) C++ (b) TensorFlow (c) Python (d) DataRobot | c |
| iv. | Which of the following is true for Train-Test Split Evaluation? (a) The procedure involves taking a dataset and dividing it into two subsets. (b) The train-test procedure is appropriate when there is a small dataset. (c) The objective is to estimate the performance of the user. (d) It cannot be used for classification or regression problems. | b |
| v. | ______ is the last stage of the AI model life cycle. (a) Scoping (b) Design (c) Deployment (d) Build | c |
| vi. | Study the following graph:  What do the dots represent in the above figure? (a) Actual values (b) Set of predicted values (c) They represent the error (d) Values at Y axis | a |
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.
| Q 6. | Define any two of the following: (a) Self-management (b) Self-awareness (c) Motivation | 2 |
| Ans: | (a) Self-management, which is also referred to as ‘self-control’, is the ability to control one’s emotions, thoughts, and behaviour effectively in different situations. This includes motivating oneself and working towards achieving personal and academic goals. (b) Self-awareness: Self-awareness is about understanding one’s own needs, desires, habits, traits, behaviours and feelings, and make the best out of one’s strengths. (c) Motivation: Motivation is derived from the word ‘motive’. Thus, directing behaviour towards certain motive or goal is the essence of motivation. An individual’s motivation may come from within (intrinsic motivation) or be inspired by others or events (extrinsic motivation). | |
| Q 7. | Mention any two ways to maintain positive attitude. | 2 |
| Ans: | Following are some ways that can help one maintain a positive attitude. * Start the day with a morning routine. * Feed the mind with positivity. * Be proactive. * Focus on constructive and positive things. * Learn from failures. * Learn to focus on the present. * Move towards your goals and dreams. | |
| Q 8. | Differentiate between a worksheet and a workbook. | 2 |
| Ans: | Worksheet: A worksheet is a collection of cells in the form of a grid (a network of lines that intersect each other, making rectangles). When you open a spreadsheet for the first time, you see a blank worksheet with the name ‘Sheet1’. Workbook: A workbook is a spreadsheet that has one or more worksheets. | |
| Q 9. | Mention any two characteristics of entrepreneurship. | 2 |
| Ans: | Characteristics of entrepreneurship are- (i) It is an economic activity done to create, develop and maintain a profit-oriented organisation. (ii) It begins with identifying an opportunity as a potential to sell and make profit in the market. (iii) It deals with optimisation in utilisation of resources. (iv) It is the ability of an enterprise and an entrepreneur to take risks. | |
| Q 10. | What are Startups? | 2 |
| Ans: | A startup is a company that is in the first stage of its operations. A startup and a traditional business venture are different, most notably for the way they think about growth. A startup is often financed by the founders until the business gets off the ground, and it gets outside finance or investments. |
Answer any 4 out of the given 6 questions in 20 – 30 words each (2 x 4 = 8 marks)
| Q 11. | What is Design thinking? | 2 |
| Ans: | Design Thinking is a design methodology that provides a solution-based approach to solving problems. It’s extremely useful in tackling complex problems that are ill-defined or unknown. The five stages of Design Thinking are as follows: (a) Empathize, (b) Define, (c) Ideate, (d) Prototype, and (e) Test. | |
| Q 12. | Explain the term Train-Test Split Evaluation. | 2 |
| Ans: | The train-test split is a technique for evaluating the performance of a machine learning algorithm. It can be used for classification or regression problems and can be used for any supervised learning algorithm. The procedure involves taking a dataset and dividing it into two subsets. (i) The first subset is used to fit the model and is referred to as the training dataset. (ii) The second subset is not used to train the model; instead, the input element of the dataset is provided to the model, then predictions are made and compared to the expected values. This second dataset is referred to as the test dataset. | |
| Q 13. | Give any two factors that make storytelling a powerful tool. | 2 |
| Ans: | The factors that make storytelling powerful are its attribute to make information more compelling, the ability to present a window in order to take a peek at the past, and finally to draw lessons and reimagine the future by affecting necessary changes. | |
| Q 14. | Differentiate between Train dataset and Test dataset. | 2 |
| Ans: | Train Dataset: Used to fit the machine learning model. Test Dataset: Used to evaluate the fit machine learning model. | |
| Q 15. | What is Cross-Validation Procedure? | 2 |
| Ans: | Cross-validation is used to validate the model. It is the extended approach of Train Test Split evaluation. In cross-validation, we run our modeling process on different subsets of the data to get multiple measures of model quality.  For example, we could have 5 folds or experiments. We divide the data into 5 pieces, each being 20% of the full dataset. | |
| Q 16. | Mention one reason why scoping is one of the most important parts of your AI project. | 2 |
| Ans: | The first fundamental step when starting an AI initiative is scoping and selecting the relevant use case(s) that the AI model will be built to address. Reason: This stage involves the planning and motivational aspects of your project. It is important to start strong if you want your artificial intelligence project to be successful. |
Answer any 3 out of the given 5 questions in 50– 80 words each (4 x 3 = 12 marks)
| Q 17. | The following is the diagram depicting the foundational methodology of data science.  The diagram is marked with A, B, C, D. Identify these steps and briefly explain the significance of steps marked as ‘A’ and ‘B’. | 4 |
| Ans: | A => Analytic Approach B => Data Requirement C => Data Preparation D => Evaluation Significance of – (a) Analytic Approach: After clearly stating a business problem, the data scientist can define the analytic approach to solving it. Expressing the problem in the context of statistical and machine learning techniques so that the data scientist can identify techniques suitable for achieving the desired outcome. (b) Data Requirement: In this phase the data requirements are revised and decisions are made as to whether or not the collection requires more or less data. Once the data ingredients are collected, the data scientist will have a good understanding of what they will be working with. | |
| Q 18. | Mention any four considerations that should be kept in mind during the testing phase. | 4 |
| Ans: | Ans: Consideration that should kept in mind during the testing phase are – The volume of test data can be large, which presents complexities. Human biases in selecting test data can adversely impact the testing phase, therefore, data validation is important. Your testing team should test the AI and ML algorithms keeping model validation, successful learnability, and algorithm effectiveness in mind. Regulatory compliance testing and security testing are important since the system might deal with sensitive data, moreover, the large volume of data makes performance testing crucial. You are implementing an AI solution that will need to use data from your other systems, therefore, systems integration testing assumes importance. Test data should include all relevant subsets of training data, i.e., the data you will use for training the AI system. Your team must create test suites that help you validate your ML models. | |
| Q 19. | Explain the main stages of the AI Model Life cycle. | 4 |
| Ans: | Data storytelling has acquired a place of importance because: (i) It is an effective tool to transmit human experience. Narrative is the way we simplify and make sense of a complex world. It supplies context, insight, and interpretation—all the things that make data meaningful, more relevant and interesting. (ii) No matter how impressive an analysis, or how high-quality the data, it is not going to compel change unless the people involved understand what is explained through a story. (iii) Stories that incorporate data and analytics are more convincing than those based entirely on anecdotes or personal experience. (iv) It helps to standardize communications and spread results. (v) It makes information memorable and easier to retain in the long run. | |
| Q 20. | Mention any four reasons due to which data storytelling has acquired a place of importance. | 4 |
| Ans: | Data storytelling has acquired a place of importance because: (i) It is an effective tool to transmit human experience. Narrative is the way we simplify and make sense of a complex world. It supplies context, insight, and interpretation—all the things that make data meaningful, more relevant, and interesting. (ii) No matter how impressive an analysis, or how high-quality the data, it is not going to compel change unless the people involved understand what is explained through a story. (iii) Stories that incorporate data and analytics are more convincing than those based entirely on anecdotes or personal experience.It helps to standardize communications and spread results. (iv) It makes information memorable and easier to retain in the long run. | |
| Q 21. | Consider the following graph.  Mention the steps that can assist in finding compelling stories in the data sets. | 4 |
| Ans: | Steps that can assist in finding compelling stories in the data sets are as follows: Step 1: Get the data and organise it. Step 2: Visualize the data. Step 3: Examine data relationships. Step 4: Create a simple narrative embedded with conflict. |
