Are you a Class 12 student preparing for the CBSE Artificial Intelligence (AI – Code 843) exam? You’re in the right place! We’ve uploaded the complete solution of the CBSE Class 12 AI Previous Year Question Paper 2024–25 session, based on the official paper conducted by the CBSE board.
Our expert team has solved each question in a clear, student-friendly manner, following the updated CBSE guidelines. Whether you’re revising or solving past papers for practice, this will boost your preparation and confidence.
Series 1XYXW
Question Paper Code 367 Set 4
ARTIFICIAL INTELLIGENCE
(Session 2024-25)
Time allowed : 2 hours
Maximum 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)
1. Answer any 4 out of the given 6 questions on Employability Skills. 4×1=4
(i) Communication involves a sender, who encodes and send a message through a channel, and a receiver, who decors the message and gives _____.
a) Message
b) Feedback
c) Signal
d) Output
(ii) _____ is a kind of motivation that includes activities for which there is no apparent reward but one derives enjoyment and satisfaction in doing them.
a) Intrinsic
b) Extrinsic
c) Positive
d) Self
(iii) Rakhi is not able to trust anyone, not even friends or family members. She holds gurdges against others. What is the kind of personality disorder that she suffers from?
a) Schizoid
b) Paranoid
c) Dependent
d) Obessive
(iv) Varsha has created a spreadsheet on a laptop that she is shared by her group members. She does not want anyone to open or edit her file. How can she protect her file?
Ans: File tab > Save As > Tools> General Options > Type and Confirm Password > Save
(v) Which of the following is not an environmental barrier for an entrepreneur?
a) Availability of skilled labour
b) Lack of adequate raw material
c) Lack of requisite machinery
d) Unavailability of money on time
(vi) Which of the following is not a Greenhouse gas?
a) Carbon dioxide
b) Methane
c) Oxygen
d) Nitrous oxide
2. Answer any 5 out of the given 6 questions. 5×1=5
(i) Statement-I: A capstone project is the final project of an academic program.
Statement-II: For a capstone project, the students research on a topic independently.
a) Both statement I and statement II are correct
b) Both statement I and statement II are incorrect
c) Statement I is correct but statement II is incorrect
d) Statement II is correct but statement I is incorrect
(ii) What are three key elements of data storytelling?
a) Data, visuals and narrative
b) Data, charts and statistics
c) Data, algorithms and visualisation
d) Data, graphs and reports
(iii) Which of the following is true about RMSE?
a) It helps to find the square root of a number
b) It stands for Rough Mean Square Error
c) It helps to determine the accuracy of an AI model
d) It is the square root of the sum of test values and predicted values
(iv) Which of the following is not one of the three main stages of an AI project’s life cycle?
a) Project scoping
b) Data visualisation
c) Design or build phase
d) Deployment in production
(v) At high level, any AI project follows 6 steps. What is the first step in the AI project process?
a) Data gathering
b) AI model construction
c) Problem definition
d) Deployment
(vi) Which of the following is true about Design or Build stage of an AI project life-cycle?
a) It is the first stage
b) It is an iterative process
c) It takes 15 days to complete
d) It includes only data acquisition and exploration
3. Answer any 5 out of the given 6 questions. 5 x 1=5
(i) Which of the following is not one of the six steps in an AI project?
a) Data gathering
b) Data cleaning
c) Evaluation and refinements
d) Deployment
(ii) Why is narrative important in data storytelling?
a) It increases the volume of data
b) Its supplies context, inside and interpretation to make data meaningful
c) It eliminates the need for data visualisation
d) It automaates the data analysis process
(iii) What does the phrase “garbage in, garbage out” mean in the context of an AI project?
a) If the data collected his bad, the AI model will not be effective
b) If you select the wrong AI model, the project will fail
c) AI algorithms and correct bad data inputs automatically
d) Garbage data should be avoided in the deployment phase
(iv) What is one of the long-term benefits of data storytelling?
a) It generates more data
b) It makes information more memorable and easier to retain
c) It eliminate the need for analysis
d) It simplifies the data collection process
(v) Design thinking is extremely useful in tackling complex problems that all ill-defined or unknown. What is the primary focus of design thinking?
a) Aesthetics of design
b) Solution based approach to problem solving
c) Technical coding skills
d) Project management
(vi) Which of the following is NOT a key activity during the scoping phase of an AI model life-cycle?
a) Defining the business objectives
b) Aligning stakeholders’ expectations
c) Cleaning and preparing the data
d) Evaluating Return On Investment (ROI)
4. Answer any 5 out of the given 6 questions. 5×1=5
(i) The _____ stage of an AI project cycle involves the planning and motivational aspects of your project.
a) Design
b) Deployment
c) Testing
d) Requirement analysis
(ii) _____ is a structured approach for communicating insights drawn from data, combined with visuals and narratives.
a) Graphs
b) Data storytelling
c) Data requirements
d) Data acquisition
(iii) A good model should have an RMSE value less than _____.
a) 160
b) 170
c) 180
d) 190
(iv) The narrative is companied with ______ , to explain why a particular insight has been generated.
a) Scores
b) Probability
c) Data
d) Project
(v) Which of the following is not an AI development platform?
a) Google Cloud AI platform
b) IBM Watson developer platform
c) Infosys Nia Resources
d) Alexa AI
(vi) Assertion (A): MSE is a regression loss function
Reason (R): It is not good to use MSE, if your target data is normally distributed around a mean value
Select the appropriate option for the statement 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
5. Answer any 5 out of the given 6 questions. 5×1=5
(i) Match the following:
Options:
a) a-i, b-ii, c-iii
b) a-ii, b-i, c-iii
c) a-iii, b-i, c-ii
d) a-iii, b-ii, c-i
(ii) State true or false
If there is more pattern in the data, then AI development techniques may be employed.
Ans: False
(iii) Which of the following is not one of the open frameworks used in AI model building?
a) Tensor flow
b) Apple Siri
c) Scikit-learn
d) XG Boost
(iv) Design thinking is a 5-stage process. Which of the following is the first stage and last stage respectively?
a) Empathize, Test
b) Empathize, Prototype
c) Define, Prototype
d) Define, Test
(v) State true or false
Human Biases in selecting test data can adversely impact the testing phase.
Ans: True
(vi) Which of the following analytical approach should be used to show relationship?
a) Predictive
b) Classification
c) Descriptive
d) Statistical analysis
Section – B (Subjective Type Questions)
Answer any 3 out of the given 5 questions on Employability Skills. 3×2=6
Answer each question in 20-30 words :
6. There are five stages of listening. The first stage is ‘Receiving’. Write the names of other four stages.
Ans: The stages of active listening are as follows.
Responding, Understanding, Remembering, Evaluation
7. Explain the term: Personality traits. Name any two parameters that describe a personality, based on five Factor Model.
Ans: Personality traits are defined as relatively lasting patterns of thoughts, feelings, and behaviours that distinguish individuals from one another.
Parameters (Any two) – Openness, consciousness, Extraversion, Agreeableness, Neuroticism
8. Write steps to print a presentation.
Ans: Step 1: Click File button and click Print option. Print dialog box is displayed
Step 2: Select number of copies and other required options.
Step 3: Click on Print button.
9. List any four qualities of a successful entrepreneur.
Ans: Qualities of a successful entrepreneur are:
i) Self-confidence, ii) Initiative, iii) Risk taker, iv) Ability to learn from experience, v) Decision-making ability
10. Write any two ways to minimize waste and pollution in manufacturing plants and factories.
Ans: i) Managing E-waste, ii) Use of eco-friendly material
Answer any 4 out of the given 6 questions in 20-30 words each. 4×2=8
11. Briefly explain the cross validation procedure to validate a model.
Ans: In cross-validation, we run our modeling process on different subsets of the data to get multiple measures of model quality
12. What is Train-Test split evaluation? What are the two types of problems for which Train-Test Split Evaluation can be used?
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.
13. Wrirte any two factors that make storytelling powerful and integral part of indigenous culture.
Ans: (Any two) i) Its attribute to make information more compelling
ii) It shapes, empowers, and connects people.
iii) Its ability to present a window in order to take a peek in the past.
iv) To draw lessons
v) To reimagine the future by affecting necessary changes.
14. Draw a diagram to represent foundational methodology for Data Science.
15. “Time series decomposition involves thinking of a series as a combination of level, trend, seasonality and noise components.” Define any two of these components.
Ans: These components are defined as follows : (Any two)
i) Level : The average value in the series.
ii) Trend : The increasing or decreasing value in the series.
iii) Seasonality : The repeating short-term cycle in the series.
iv) Noise : The random variation in the series.
16. Give any two examples of each of the following with respect to evaluation of AI development platforms.
a) Open Languages
Ans: Python, R, Scala
b) Productivity Enhancing Capabilities
Ans: Auto AI, Hyperparameter Optimization, Visual Modelling
Answer any 3 out of the given 5 questions in 50-80 words each. 3×4=12
17. List down the steps that can assist in finding compiling stories in the data sets.
Ans: Some easy 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
18. a) What is a loss function? Write the two categories of loss functions.
Ans: A loss function is a measure of how good a prediction model does in terms of being able to predict the expected outcome.
Two categories: Classification and Regression Loss.
b) Explain, with an example, when to use MSE as the loss function.
Ans: MSE is used when doing regression:
(i) believing that your target, conditioned on the input, is normally distributed
(ii) wants large errors(Outliers) to be significantly more penalized than small ones.
Example: when you want to predict future house price. The price is a continuous value, and so we want to do regression. Hence MSE can be used as loss function.
19. Explain the following stages of every AI project life cycle.
a) Requirements Analysis
Ans: Scoping (Requirements analysis) 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. This is arguably the most important part of your AI project.
1. 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.
2. In this phase, it’s crucial to precisely define the strategic business objectives and desired outcomes of the project, select align all the different stakeholders’ expectations, anticipate the key resources and steps, and define the success metrics.
3. Selecting the AI or machine learning use cases and being able to evaluate the return on investment (ROI) is critical to the success of any data project.
b) Building the Model
Ans: Design of 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 : data acquisition, exploration, preparation, cleaning, feature engineering, testing and running a set of models to try to predict behaviours or discover insights in the data.
20. Picking an Analytic Approach to solve a problem is based on the type of question.
Explain the given statement with suitable examples.
Ans: Selecting the right analytic approach depends on the question being asked. Once the problem to be addressed is defined, the appropriate analytic approach for the problem is selected in the context of the business requirements. This is the second stage of the data science methodology.
> If the question is to determine probabilities of an action, then a predictive model might be used.
> If the question is to show relationships, a descriptive approach may be required.
> Statistical analysis applies to problems that require counts: if the question requires a yes/no answer then a classification approach to predicting a response would be suitable.
Suggested examples: (a) Sale/launch of a product (b) Stock Prices (c) Cricket Match Score (etc)
21. a) How do good stories emerge?
b) Which of the following is a better data story? Give reasons.
Ans (a): Good stories don’t just emerge from data itself; they need to be unravelled from data relationships. Closer scrutiny helps uncover how each data point relates with others.
Ans (b): Option 2 is a better data story as it is explaining what is depicted in the graph.