CBSE Class 12 Artificial Intelligence (Code 843) Sample Question Paper 2024-25 with Solution is an essential resource for students preparing for board examinations. Sample papers are officially designed based on the latest CBSE exam pattern, helping students understand the structure, marking scheme, and types of questions that may appear in the final exam. By practicing this sample question paper, students can improve their time management skills and gain confidence before the actual board exam.
This Class 12 Artificial Intelligence 843 Sample QP 2024-25 with Solution includes a variety of questions such as objective-type questions, case-based questions, and subjective questions, covering all important units of the syllabus. The provided detailed solutions help students understand the correct answering techniques and concepts clearly. Regular practice of such papers not only enhances problem-solving ability but also helps in identifying weak areas for improvement.
CBSE Class 12 AI 843 Sample QP 2024-25 with Solution
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Note: The CBSE Class 12 Artificial Intelligence (Code 843) Sample Question Papers for sessions 2024-25 and 2023-24 are identical, so downloading both is unnecessary and may waste your valuable time.
The Year-Wise CBSE Class 12 Artificial Intelligence (843) Pre-Board and Sample Question Papers with Solutions are provided at the bottom of this post.
CBSE Class 12 AI 843 Sample Question Paper Session (2024-25)
CBSE | DEPARTMENT OF SKILL EDUCATION
ARTIFICIAL INTELLIGENCE (SUBJECT CODE - 843)
Sample Question Paper (SQP) Solution for Class XII (Session 2024-2025)
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):
- This section has 05 questions.
- Marks allotted are mentioned against each question/part.
- There is no negative marking.
- Do as per the instructions given.
- SECTION B – SUBJECTIVE TYPE QUESTIONS (26 MARKS):
- This section has 16 questions.
- A candidate has to do 10 questions.
- Do as per the instructions given.
- Marks allotted are mentioned against each question/part.
SECTION A - OBJECTIVE TYPE QUESTIONS
Q.1 Answer any 4 out of the given 6 questions on Employability Skills. (1X4=4 Marks)
i. An indirect object answers the questions, such as
a) What?
b) Why?
c) To whom?
d) Which?
ii. “I enjoy singing and practice it as it gives me a lot of pleasure. It also works as a stress buster.” The sentence given above is an example of
a) Intrinsic motivation
b) Extrinsic motivation
c) External motivation
d) Lack of motivation
iii. Statement 1: Personality traits are defined as relatively lasting patterns of thoughts, feelings and behaviors.
Statement 2: They distinguish individuals from one another.
a) Both Statement 1 and Statement 2 are correct
b) Both Statement 1 and Statement 2 are incorrect
c) Statement 1 is correct but Statement 2 is incorrect
d) Statement 2 is correct but Statement 1 is incorrect
iv. Match the following:
| A. To underline text | 1. Ctrl + B |
| B. To make text bold | 2. Ctrl + I |
| C. To make text italic or slanting | 3. Ctrl + U |
a) A - 2; B - 3; C - 1
b) A - 3; B - 1; C - 2
c) A - 1; B - 3; C – 2
d) A - 1; B - 2; C - 3
v. After 20 years of being a successful entrepreneur in Lucknow, Ravi decided to move back to his village. He opened a clothing store but people in his village said that the style did not match what they wanted. They wanted more variety and brighter colours. So, he sold off the old clothes to his friend in a city and bought good quality clothes from a local seller.
Which attitude can you witness in Ravi?
a) Interpersonal skills
b) Perseverance
c) Competitiveness
d) Barrier
vi. Electronic waste, as known as e-waste, is generated when any electronic or electrical equipment becomes unfit for the intended use or if it has crossed its expiry date.
Due to rapid technological advancements and the production of newer electronic equipment, the old ones get easily replaced with new models. It has particularly led to an exponential increase in e-waste in India. Which of the following is the correct way to handle e-waste?
a) Sell the e-waste to a local scrap dealer
b) Throw the e-waste in the dustbin
c) Dispose-off the e-waste with the help of a certified partner
d) Dump the e-waste in the local landfill
Q.2 Answer any 5 out of the given 6 questions. (1X5=5 Marks)
i. In Design Thinking, ____ phase involves gathering user feedback on the prototypes you've created as well as obtaining a better understanding of your users.
a) Prototype
b) Test
c) Ideate
d) Empathize
ii. _______ is the first step involved in telling an effective data story.
a) Creating visuals
b) Adding narrative
c) Understanding the Audience
d) Gathering data
iii. Match the following
| 1. Which category? | A. (Anomaly Detection) |
| 2. How much or how many? | B. (Regression) |
| 3. Which group? | C. (Recommendation) |
| 4. Is this unusual? | D. (Classification) |
| 5. Which option should be taken? | E. (Clustering) |
a) 1=D, 2=B, 3=E, 4=A, 5=C
b) 1=C, 2=D, 3=B, 4=E, 5=A
c) 1=D, 2=B, 3=C, 4=E, 5=A
d) 1=E, 2=A, 3=D, 4=C, 5=B
iv. Identify two AI development tools from the following:
(i) DataRobot (ii) Python (iii) Scikit Learn (iv) Watson Studio
a) (i) & (ii)
b) (ii) & (iii)
c) (i) & (iii)
d) (i) & (iv)
v. You want to predict future house prices. The price is a continuous value, and therefore we want to do regression. Which loss function should be used here?
a) RMSE
b) MSE
c) Exponential error
d) MAE
vi. The design phase of the AI Model Life Cycle is an ______ process.
a) compact
b) permanent
c) periodic
d) iterative
Q.3 Answer any 5 out of the given 6 questions. (1X5=5 Marks)
i. Techniques like descriptive statistics and visualisations can be applied to datasets after the original data gathering to analyse the content. To close the gap, additional data collecting may be required. Identify the stage of this analytic approach.
a) Data Requirements
b) Data Gathering
c) Data Understanding
d) Data Preparation
ii. Stories create _______ experiences that transport the audience to another space and time.
a) unpleasant
b) tedious
c) repetitive
d) engaging
iii. In this phase, we define the project's strategic business objectives and desired outcomes, align all stakeholders' expectations as well as establish success metrics. Identify this phase of the AI Model Life Cycle.
a) Design
b) Scoping
c) Evaluation
d) Data Collection
iv. Assertion (A): Stories that combine statistics and analytics are more persuasive.
Reason (R): When we talk about data storytelling, we're talking about stories in which data plays a central role.
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 A 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
v. Which of the following is not a feature of RMSE?
a) It tells about the accuracy of the model
b) Higher value means hyper parameters need to be tweaked
c) Lower RMSE values are not good for the AI model
d) RMSE is a measure of how evenly distributed residual errors are
vi. Once you have got an AI model that's ready for production, AI engineers then ____ a trained model, making it available for external inference requests.
a) Evaluate
b) Test
c) Deploy
d) Redesign
Q.4 Answer any 5 out of the given 6 questions. (1X5=5 Marks)
i. Data Validation for human biases is conducted in _________ phase of AI Model Life Cycle.
a) Scoping
b) Data Collection
c) Design
d) Testing
ii. Identify the following icons:
Ans: (a) Narrative (b) Data
iii. Which of the following is a disadvantage of Cross Validation Technique?
a) Cross-validation provides insight into how the model will generalise to a new dataset
b) Cross-validation aids in determining a more accurate model prediction performance estimate
c) As we need to train on many training sets, cross-validation is computationally expensive
d) Cross-validation could result in more precise models
iv. Hyper parameters are parameters whose values govern the learning process.
a) True
b) False
v. The steps that assist in finding compelling stories in the data sets are as follows. Arrange them in proper order:
(i) Visualize the data.
(ii) Examine data relationships.
(iii) Get the data and organise it.
(iv) Create a simple narrative embedded with conflict.
a) (i)-(ii)-(iii)-(iv)
b) (ii)-(iii)-(i)-(iv)
c) (iv)-(i)-(iii)-(ii)
d) (iii)-(i)-(ii)-(iv)
vi. Choose the difference between Regression and Classification Loss functions from the following:
a) Regression functions predict a quantity, and classification functions predict a label
b) Regression functions predict a label, and classification functions predict a quantity
c) Regression functions predict a qualitative value, and classification functions predict a label
d) Regression functions predict a label, and classification functions predict a qualitative value
Q.5 Answer any 5 out of the given 6 questions. (1X5=5 Marks)
i. Stories change the way that we interact with data, transforming it from a dry collection of ______ to something that can be entertaining, thought provoking, and inspiring change.
a) visuals
b) points
c) images
d) facts
ii. A good model should have an _____ value less than 180.
a) RMSE
b) MSE
c) Focal Loss
d) MAE
iii. Which of the following is incorrect?
(i) Testing data is the one on which we train and fit our model basically to fit the parameters
(ii) Training data is used only to assess performance of model
(iii) Testing data is the unseen data for which predictions have to be made
a) (i) and (iii) only
b) (i) and (ii) only
c) (ii) and (iii) only
d) (i), (ii) and (iii)
iv. Choose an example of an AI predictive model.
a) YouTube
b) Spam detection
c) weather forecast
d) Sentiment Analysis
v. Which of the following are the objectives of the testing team in AI modelling?
(i) Model Validation
(ii) Security compliance
(iii) Understanding data
(iv) Minimizing bias
a) (i), (ii) and (iii)
b) (ii), (iii) and (iv)
c) (i), (iii) and (iv)
d) (i), (ii) and (iv)
vi. If AI techniques are to be applied to a dataset, the data must have a _______.
a) association
b) relationship
c) pattern
d) Either a and b
SECTION B - SUBJECT TYPE QUESTIONS
Answer any 3 out of the given 5 questions on Employability Skills. (2x3=6 Marks)
Answer each question in 20-30 words.
Q.6 What does ‘P’ stand for in the acronym ‘RESPECT’ used to ensure active listening? Explain.
Ans: P in RESPECT stands for - Pay attention and focus on what the speaker is saying.
Q.7 Shikha is an elderly woman. She stays with her family. She has a habit of washing her hands at least 20 times a day. Even after washing her hands, she feels they are not clean, and continues rubbing or washing them. She neither talks to her grandchildren, nor does she participate in any family activity. Suggest her one way in which she can overcome her personality disorder.
Ans: (i) Talk to someone. Most often, it helps to share your feelings.
(ii) Look after your physical health. A healthy body can help you maintain a healthy mind.
(iii) Stay positive by choosing words like ‘challenges’ instead of ‘problems’.
Q.8 Differentiate between the terms worksheet and workbook.
Ans: A worksheet is a collection of cells in the form of a grid. When you open a spreadsheet for the first time, you see a blank worksheet with the name ‘Sheet1’.
A workbook is a spreadsheet that has one or more worksheets.
Q.9 Name two government schemes that help small-scale entrepreneurs gain capital.
Ans: (i) Pradhan Mantri Mudra Yojana (PMMY)
(ii) Prime Minister’s Employment Generation Programme (PMEGP)
(iii) Credit Guarantee Fund Trust for Micro and Small Enterprises (CGTMSE)
(iv) Startup India Initiative
Q.10 The greening of economy presents a major opportunity to start new businesses, develop new markets and lower energy costs. Write any two benefits of green jobs.
Ans: (i) increase the efficiency of energy and raw material.
(ii) reduce greenhouse gas emissions.
(iii) control waste and pollution.
(iv) protect and restore ecosystems.
Answer any 4 out of the given 6 questions in 20-30 words each. (2x4=8 Marks)
Q.11 Define capstone project.
Ans: A capstone project is a project in which students independently research a topic to gain a deep understanding of the subject. It allows them to integrate their knowledge and demonstrate it through a comprehensive project.
Q.12 Can MSE be a negative value? Give reasons.
Ans: No, MSE (Mean Squared Error) cannot be negative because the differences between actual and predicted values are squared. Squaring always gives a non-negative value (zero or positive), so MSE is always zero or positive.
Q.13 What is the importance of a narrative in a story?
Ans: A narrative is important because it helps present information in a clear and meaningful way. It connects data with context, reduces confusion, and makes the message more effective and easy to understand.
Q.14 Imagine that you want to create your first app. Create a list of questions you would develop to decompose this task.
Ans: To decompose the task of creating an app, we can ask these questions:
What kind of app do I want to create?
What will the app look like (design/interface)?
Who is the target audience?
What graphics will be used?
What audio or features will be included?
Q.15 Differentiate between training set and test set.
Ans: Training Set: It is the dataset used to train the machine learning model. It contains data with known outcomes.
Test Set: It is the dataset used to evaluate the performance of the trained model on new, unseen data.
Q.16 “Once the relevant projects have been selected and properly scoped, the next step of the machine learning lifecycle is the Design or Build phase.” Briefly explain this phase.
Ans: The Design (or Build) phase is an iterative process where the machine learning model is developed. It includes steps like data collection, data cleaning, preparation, feature engineering, and testing different models to find the best results.
Answer any 3 out of the given 5 questions in 50-80 words each. (4x3=12 Marks)
Q.17 Explain how data storytelling can bring about change using a diagram.
Ans: Data storytelling is a structured approach for communicating insights drawn from data, and invariably involves a combination of three key elements: data, visuals, and narrative. When the narrative is accompanied with data, it helps to explain the audience what’s happening in the data and why a particular insight has been generated. When visuals are applied to data, they can enlighten the audience to the insights that they wouldn’t perceive without the charts or graphs.
Finally, when narrative and visuals are merged together, they can engage or even entertain an audience. When you combine the right visuals and narrative with the right data, you have a data story that can influence and drive change.
Q.18 Consider the following data
| x | y |
|---|---|
| 44 | 47 |
| 46 | 48 |
| 48 | 55 |
| 50 | 58 |
| 52 | 49 |
Regression Equation: 0.7x + 17.8
Calculate the RMSE(Root means Square Error) for the above data.
Ans: Calculate predicted values (ŷ = 0.7x + 17.8)
x=44 → ŷ=48.6
x=46 → ŷ=50.0
x=48 → ŷ=51.4
x=50 → ŷ=52.8
x=52 → ŷ=54.2
Calculate squared errors (y − ŷ)²
(47 − 48.6)² = 2.56
(48 − 50)² = 4
(55 − 51.4)² = 12.96
(58 − 52.8)² = 27.04
(49 − 54.2)² = 27.04
MSE = (2.56 + 4 + 12.96 + 27.04 + 27.04) / 5 = 14.72
RMSE = √14.72 ≈ 3.84
Q.19 List the considerations which data scientists have to keep in mind during the testing stage.
Ans:
- The test data can be large, making testing complex.
- Human bias in selecting test data should be avoided; proper data validation is important.
- The model should be tested for accuracy, learning ability, and effectiveness.
- Security, performance, and regulatory compliance should be checked, especially when handling sensitive data.
Q.20 Explain the Cross Validation Procedure? In which situation is it better than a Train Test Split?
Ans: Cross-validation is a technique used to evaluate a model by dividing the dataset into multiple parts. In k-fold cross-validation, the data is split into k equal folds. In each iteration, one fold is used as test data and the remaining (k–1) folds are used for training. This process is repeated k times, and the final performance is calculated by taking the average of all results.
When is it better than Train-Test Split?
Cross-validation is better when the dataset is small, as it uses all data for both training and testing, giving more reliable and accurate results.
Q.21 (a) List the steps of creating an effective data story.
Ans: The steps involved in telling an effective data story are given below:
Step 1: Understanding the audience
Step 2: Choosing the right data and visualisations
Step 3: Drawing attention to key information
Step 4: Developing a narrative
Step 5: Engaging your audience
(b) Which of the following is a better data story? Give reasons.
Option A:
Option B:
Ans: Option A is a better data story.
Reasons: (i) The insight given at the bottom of the visual is giving a clear idea about context which is not there in Option B.
(ii) Option A visual provides a compelling narrative.
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