CHENNAI SAHODAYA SCHOOLS COMPLEX
COMMON EXAMINATION
Class: 12
ARTIFICIAL INTELLIGENCE (SUBJECT CODE -843)
Blue-print Max) Time: 2 Hours
Max) Marks: 50
PART A - EMPLOYABILITY SKILLS (10 MARKS):
UNIT NAME OF THE UNIT OBJECTIVE TYPE SHORT ANSWER TYPE TOTAL
NO. QUESTIONS QUESTIONS
1 MARK EACH 2 MARKS EACH
1 Communication Skills - IV 1 1 2
2 Self-Management Skills - IV 2 1 2
3 ICT Skills - IV 1 1 2
4 Entrepreneurial Skills - IV 1 1 3
5 Green Skills - IV 1 1 2
TOTAL QUESTIONS 6 5 11
NO) OF QUESTIONS TO BE Any 4 Any 3 07
ANSWERED
TOTAL MARKS 1x4=4 2x3=6 10
MARKS
PART B - SUBJECT SPECIFIC SKILLS (40 MARKS):
UNIT NAME OF THE OBJECTIVE TYPE SHORT ANSWER DESCRIPTIVE / LONG TOTAL
NO. UNIT QUESTIONS TYPE QUESTIONS ANS. TYPE QUESTIONS QUESTIONS
1 MARK EACH 2 MARKS EACH 4 MARKS EACH
1 Capstone 10 4 2 14
Project
2 Model Life 8 1 1 11
Cycle
3 Story Telling 6 1 2 10
through Data
TOTAL QUESTIONS 24 6 5 35
NO. OF QUESTIONS 20 Any 4 Any 3 27
TO BE ANSWERED
TOTAL MARKS 1 x 20 = 20 2x4=8 4 x 3 = 12 40 MARKS
CHENNAI SAHODAYA SCHOOLS COMPLEX
COMMON EXAMINATION
Class: 12
Artificial Intelligence (843)
Marking Scheme
Roll No.: Maximum Marks: 50
Date: Time allowed: 2 hours
General Instructions:
1) Please read the instructions carefully)
2) This Question Paper consists of 21 questions in two sections – Section A & Section B.
3) Section A has Objective type questions whereas Section B contains Subjective type questions.
4) Out of the given (5+16 =) 21questions, a candidate has to answer (5+10=) 15 questions in the allotted
(maximum) time of 2 hours.
5) All questions of a particular section must be attempted in the correct order.
6) SECTION A - OBJECTIVE TYPE QUESTIONS (24 MARKS):
i) This section has 05 questions.
ii) There is no negative marking.
iii) Do as per the instructions given.
iv) Marks allotted are mentioned against each question/part)
7) SECTION B – SUBJECTIVE TYPE QUESTIONS (26 MARKS):
i) This section contains 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
Q1) Answer any 4 out of the given 6 questions on Employability Skills (4x1=4 Marks)
i. Which of the following factors does not improve active listening?
a) Eye contact b) Being pre-occupied c) Gestures d) Giving feedback
ii. Janvi is feeling extremely nervous and worried because she believes that other people do not like
her or are trying to harm her. Identify the personality disorder from the following:
a) Anti-Social b) Schizoid c) Paranoid d) Narcissistic
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. Mr Gupta has a spreadsheet with a list of 500 items in his shop. A customer comes and asks for a
particular item. How should he arrange the data so that he can find that item fast? What would Mr
Gupta do? He will:
a) apply filter b) sort the data c) use password d) format data.
v. The__________ set up by the Indian government, can be utilized to provide support activities like
technology dissemination, training awareness to the local youth and farmers for collection, storage
and reuse of agro-waste)
a) Farmer Vigyan Kendras b) Krishi Vigyan Kendras
c) Indian Vigyan Kendras d) None of the above
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
Q2) Answer any 5 out of the given 6 questions (5x1 = 5 marks)
i. If the problem is to show relationships, a _________ approach may be required.
a) Predictive b) Classification c) descriptive d) statistical
ii. Every project, regardless of its size, starts with_________________, which lays the foundation for
successful resolution of the business problem.
a) business understanding b) Evaluation c) Feedback d) Data Analysing
iii. Which of the following options is/are true for K-fold cross-validation?
1) Increase in K will result in higher time required to cross validate the result.
2) Higher values of K will result in higher confidence on the cross-validation result as compared to
lower value of K.
3) If K=N, then it is called Leave one out cross validation, where N is the number of observations
a) 1 and 2 b) 2 and 3 c) 1 and 3 d) 1, 2 and 3
iv. 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
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 average value in the series in a time decomposition series is known as _______.
a) Level b) Trend c) Seasonality d) Noise
Q3) Answer any 5 out of the given 6 questions (5x1 = 5 marks)
i. ASSERTION (A): Business Understanding stage is the hardest and crucial stage in Data Science
methodology
REASON (R): Funding for Business Understanding stage is very low so it becomes hardest.
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
ii. Which one among the following is not correct regarding the Data Collection?
a) Identify the necessary data content and formats
b) Web scraping may be done on related data
c) Pandas may be used to download the data
d) Inaccessible data may be defined.
iii. A researcher wants to study the association between gender and using a mobile phone. Data
collected for this study will be _______________
a) Qualitative data b) Quantitative data c) Continuous data d) Classified data
iv. A random sample of n=6 taken from the population has the elements 6, 10, 13, 14, 18, 20. Then,
which option is False?
a) Point estimate for population mean is 13.5
b) Point estimate for population standard deviation is 4.68
c) Point estimate for population standard deviation is 3.5
d) Point estimate for standard error of mean is 1.91
v. Data Validation for human biases is conducted in _________ phase of AI Model Life Cycle.
a) Scoping b) Data Collection c) Design d) Testing
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
Q4) Answer any 5 out of the given 6 questions (5x1 = 5 marks)
i. 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
ii. ASSERTION (A): The second step of the machine learning lifecycle is the Design or Build phase.
REASON (R): The Design phase is essentially an iterative process comprising all the steps
relevant to building the AI or machine learning model
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
iii. Unscramble the letters and identify the missing stage in the process of AI project lifecycle project
scoping, deployment)
a) ESGIND b) TSET c) ESOCPGIN d) AELEVTUA
iv. In AI development which framework is used?
a) Scikit-learn b) Tkinter c) PyCharm d) Matplotlib
v. Identify two AI development tools from the following:
1) Data Robot 2) Python 3) Scikit Learn 4) Watson Studio
a) 1 & 2 b) 2 & 3 c) 1 & 3 d) 1 & 4
vi. The design phase of the AI Model Life Cycle is a process.
a) compact b) permanent c) periodic d) iterative
Q5) Answer any 5 out of the given 6 questions (5x1 = 5 marks)
i. How can data storytelling be more effective in conveying insights from data?
a) By presenting data in fragmented charts
b) By using anecdotes and personal experience
c) By combining data, visuals, and narrative
d) By keeping the data complex and technical
ii. 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
iii. Which step is NOT part of the process for identifying interesting stories in data sets?
a) Get the data and organize it b) Visualize the data
c) Examine data relationships d) Create complex narratives
iv. When visuals are applied to data, they provide __________ to audience
a) enlighten b) change c) insights d) explain
v. 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
vi. Stories create _______ experiences that transport the audience to another space and time.
a) unpleasant b) tedious c) repetitive d) engaging
SECTION B: SUBJECTIVE TYPE QUESTIONS
Answer any 3 out of the given 5 questions on Employability Skills (3x2=6marks)
Q6) Mentions the steps to be followed towards removing barriers for active listening.
• Do not let emotions take over your mind.
• Keep away phones and digital devices.
• Create a conducive environment to avoid misinterpretations and distractions.
• Avoid developing biases and be objective in your approach when interacting with others.
• Allow the other person to finish speaking, and then, respond.
Q7) 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.
Steps to overcome personality disorders
• Talk to someone. Most often, it helps to share your feelings.
• Look after your physical health. A healthy body can help you maintain a healthy mind.
• Build confidence in your ability to handle difficult situations.
• Engage in hobbies, such as music, dance and painting. These have a therapeutic effect.
• Stay positive by choosing words like ‘challenges’ instead of ‘problems.
Q8. Write down the steps to protect your spreadsheet in Calc?
1. Select Tools menu Protect document Choose whether to protect Sheet or Document.
2. If you select Sheet, the Protect Sheet dialog box appears.
3. Type the password in Password text box. Again, type the password in Confirm text box. Note
that the password is case sensitive.
4. Click OK button.
Q9. Which attitude makes a person Successful Entrepreneur?
DECISIVENESS - Ability to make quick and profitable decisions
TAKING INITIATIVE - Ability to take charge and act in a situation before others
INTERPERSONAL SKILLS - Ability to work with others
ORGANISATIONAL SKILLS - Ability to make the optimum use of time, energy and
resources to achieve the desired goals
PERSEVERANCE - Ability to continue to do something, even when it is difficult
Q10. What are the ways to reduce the amount of waste in Industries?
✓ Reusing scrap material
✓ Ensuring quality control
✓ Waste exchange
✓ Managing e-waste
✓ Use of eco-friendly material
Answer any 4 out of the given 6 questions in 20 – 30 words each (4x2=8marks)
Q11. What is design thinking? List each stage of design thinking?
Design Thinking is a design methodology that provides a solution-based approach to solving
problems. It is extremely useful in tackling complex problems that are ill-defined or unknown.
The five stages of Design Thinking are as follows: Empathize, Define, Ideate, Prototype, and Test.
Q12. List down different problem categories that come under predictive analysis? Write one example for
each?
1. Which category? (Classification) - E.g.: Spam mail classification
2. How much or how many? (Regression) - E.g.: Flight fare prediction
3. Which group? (Clustering) - E.g.: Email marketing
4. Is this unusual? (Anomaly Detection) – E.g.: Credit card fraud detection
5. Which option should be taken? (Recommendation. – Video recommendation system
Q13. Explain difference between cross validation and train test split?
On small datasets, the extra computational burden of running cross-validation isn’t a big
deal. So, if your dataset is smaller, you should run cross-validation
If your dataset is larger, you can use train-test-split method.
Q14. Imagine that you want to create your first app. Create a list of questions you would develop to
decompose this task.
To decompose this task, you would need to know the answer to a series of smaller
problems:
what kind of app you want to create?
what will your app will look like?
who is the target audience for your app?
what will the graphics will look like?
what audio will you include?
Q15. “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.
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.
Q16.What elements of data storytelling, when merged together can engage the audience?
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.
Answer any 3 out of the given 5 questions in 50– 80 words each (3x4=12marks)
Q17. How are MSE and RMSE related? What is their range? Are they sensitive to outliers?
MSE: One of the most used regression loss functions is MSE. We determine the error in Mean-Squared-
Error, also known as L2 loss, by squaring the difference between the predicted and actual values and
average it throughout the dataset.
• Squaring the error gives outliers more weight, resulting in a smooth gradient for minor errors.
• Because the errors are squared, MSE can never be negative. The error value varies from 0 to
infinity.
• The MSE grows exponentially as the error grows. An MSE value close to zero indicates a good
model.
• It is especially useful in removing outliers with substantial errors from the model by giving them
additional weight.
RMSE: The square root of MSE is used to calculate RMSE. The Root Mean Square Deviation (RMSE. is
another name for the Root Mean Square Error.
• A RMSE value of 0 implies that the model is perfectly fitted. The model and its predictions
perform better when the RMSE is low.
• A greater RMSE indicates a substantial discrepancy between the residual and the ground truth.
• The RMSE of a good model should be less than 18
Q18. Consider the following data:
Regression line equation: Y=0.681x + 15.142. Calculate MSE and RMSE from the
above information
Q19. List the considerations which data scientists have to keep in mind during the testing stage.
a. The volume of test data can be large, which presents complexities.
b. Human biases in selecting test data can adversely impact the testing phase, therefore, data
validation is important.
c. Your testing team should test the AI and ML algorithms keeping model validation, successful
learnability, and algorithm effectiveness in mind.
d. 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.
e. You are implementing an AI solution that will need to use data from your other systems, therefore,
systems integration testing assumes importance.
f. Test data should include all relevant subsets of training data, i.e., the data you will use for training
the AI system.
g. Your team must create test suites that help you validate your ML models.
Q20. Why has Data storytelling acquired a place of importance?
a) 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, interpretation—all the things that make data
meaningful, more relevant and interesting.
b) 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.
c) Stories that incorporate data and analytics are more convincing than those based entirely on
anecdotes or personal experience.
d) It helps to standardize communications and spread results.
e) It makes information memorable and easier to retain in the long run.
Q21.The graph below depicts the voting pattern of youths. Analyse the following figure and give steps
that can assist in finding compelling stories from given datasets.
The steps involved in telling an effective data story are given below:
• Understanding the audience
• Choosing the right data and visualisations
• Drawing attention to key information
• Developing a narrative
• Engaging your audience
Pie Chart is a circular representation of data.
The pie chart above clearly shows that 28.8% of youth will vote.
9.6% will not Vote
12.7% probably will not vote
26.4% probably will vote
22.5% Don’t know
1. The insight given in the Chart are clearly emphasized by its visual separation
2. The visual provides a compelling narrative.
“END OF PAPER”
