Pre Board Examination 2021
Class - X
Subject - Artificial Intelligence
Time: 2 Hours Max. Marks: 50
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 =) 21 questions, 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) Marks allotted are mentioned against each question/part.
(iii) There is no negative marking.
(iv) Do as per the instructions given.
7. 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.
SECTION A: OBJECTIVE TYPE QUESTIONS
Q. 1 Answer any 4 out of the given 6 questions on Employability Skills
(1 x 4 = 4 marks)
i) How many sustainable development goals are given by the United Nations?
a) 14
b) 15
c) 16
d) 17
ii) ____________________ includes specific information in the form of written
comments or verbal conversations.
a) Descriptive feedback
b) Request
c) Response
d) None of these
iii) Self motivation is ____________________.
a) the things you find difficult to do
b) that accept your weakness
c) the force within you that drives you to do things
d) the things we can’t do
iv) ______________is not a sustainable development goal to United Nations
a) Clean water and Sanitation
b) Gender Equality
c) Population
d) Reduced inequalities
v) Entrepreneurs are ________________ about the future and always look forward.
a) Optimistic
b) Pessimistic
c) Doubtful
d) Employer
vi) What should you do to ensure secure online transactions?
a) Lock your computer
b) Give credit card or bank details only on safe websites
c) Use anti virus
d) Do not use pirated software
Q. 2 Answer any 5 out of the given 6 questions (1 x 5 = 5 marks)
i) ________________ refers to the massive(huge) amount of data collected during
acquisition.
a) external Data
b) Internal data
c) big Data
d) exploration
ii) The __________________canvas helps you in identifying the key elements
related to the problem.
a) Problem scoping
b) 4Ws Problem
c) Project cycle
d) Algorithm
iii) A lot of times we are unable to observe any problem in our surroundings. In that
case, we can take a look at the ____________________.
a) Sustainable Development Goals
b) Problem scoping
c) Evaluation
d) stakeholders
iv) ____________is defined as the percentage of correct predictions out of all
the observations.
a) Predictions
b) Accuracy
c) Reality
d) F1 Score
v) _________________is the sub-field of AI that is focused on enabling
computers to understand and process human languages.
a) Deep Learning
b) Machine Learning
c) NLP
d) Data Sciences
vi) Every photograph, in digital form, is made up of __________________.
a) Kernel
b) Convolution
c) Pixels
d) Greyscale
Q. 3 Answer any 5 out of the given 6 questions (1 x 5 = 5 marks)
i) Expand NLTK_______________
a) Natural Language Toolkit
b) National Language Toolkit
c) Natural Language Toolbar
d) National Language Tutorial
ii) Name any 2 methods of collecting data.
a) Surveys and Interviews
b) Rumors and Myths
c) AI models and applications
d) Imagination and thoughts
Iii) In image processing, a kernel matrix is used for
a) saving image at appropriate location
b) making duplicate image
c) deleting image copies
d) adding effects like blurring, sharpening, edge detection, and more.
iv) What will be the outcome, if the Prediction is “Yes” and it matches with the
Reality? What will be the outcome, if the Prediction is “Yes” and it does not
match the Reality?
a) True Positive, True Negative
b) True Negative, False Negative
c) True Negative, False Positive
d) True Positive, False Positive
v) Precision-Evaluation method is
a) defined as the fraction of positive cases that are correctly identified.
b) defined as the percentage of true positive cases versus all the cases
where the prediction is true.
c) defined as the percentage of correct predictions out of all the
observations.
d) comparison between the prediction and reality
vi) Give 2 examples of Supervised Learning models.
a) Classification and Regression
b) Clustering and Dimensionality Reduction
c) Rule Based and Learning Based
d) Classification and Clustering
Q. 4 Answer any 5 out of the given 6 questions (1 x 5 = 5 marks)
i) Define Neural Network.
a) Neural networks are a series of algorithms that mimic the operations of a human
brain to recognize relationships between vast amounts of data.
b) Neural network refers to any technique that enables computers to mimic human
intelligence.
c) Neural network refers to computer systems (both machines and
software) enables machines to perform tasks for which it is
programmed.
d) It refers to projects that allow the machine to work on
a particular logic.
ii) Bag of words helps in
a) Determining frequency of words in corpus
b) Tokenization
c) Stemming
d) lemmatization
iii) Decision tree is an example of
a) Ruled Based approach
b) learning based approach
c) Supervised learning
d) Unsupervised learning
iv) There are two types of pooling which can be performed on an image
a) Max pooling and average pooling
b) Sum pooling and Difference pooling
c) Additive pooling and subtractive pooling
d) Structured pooling and unstructured pooling
v) TF-IDF, which stands for term frequency — inverse document frequency, is a scoring
measure widely used to
a) classify the type and genre of a document.
b) reflect how relevant a term is in a given document( to identify stopwords).
c) understand the reliability of any AI model
d) extract the important information out of a corpus.
vi) Which of the following is not part of the AI Project Cycle?
a) Data Exploration
b) Modelling
c) Testing
d) Problem Scoping
Q. 5 Answer any 5 out of the given 6 questions (1 x 5 = 5 marks)
I) ________________________ refers to the AI modelling where the machine
learns by itself.
a) Learning Based
b) Rule Based
c) Machine Learning
d) Data Sciences
ii) Prediction and Reality can be easily mapped together with the help of :
a) Prediction
b) Reality
c) Accuracy
d) Confusion Matrix
iii) ___________________ is an example of Applications of Computer Vision.
a) Self driving car
b) Evaluation
c) Deep Learning
d) Problem Scoping
iv) _________________ is the first stage of the AI project Life cycle.
a) Problem Scoping
b) Evaluation
c) Modelling
d) Data Acquisition
v) We use __________________, a type of convolutional layer, when we need to crop
the size of volume which can make computation quicker and reduces memory. a)
Input Layer
b) Pool Layer
c) Fully Connected Layer
d) None of the above
vi) ___________ is used for finding the frequency of words in some given text sample.
a) Stemming
b) Lemmetisation
c) Bags Of Words
d) All of the Above
SECTION B: SUBJECTIVE TYPE QUESTIONS
Answer any 3 out of the given 5 questions on Employability Skills (2 x 3 = 6
marks)
Part A: Employability Skills
Q. 6 List any four skills that are required to protect your data.
Q. 7 List any four activities that help in stress management.
Q. 8 What measures should be adopted by cities to protect the environment while
ensuring development?
Q. 9 Name any four qualities of a successful entrepreneur.
Q. 10 Name any four types of verbal communication..
Answer any 4 out of the given 6 questions in 20 – 30 words each (2 x 4 = 8 marks)
Q. 11 Write a short note on chatbots.
Q. 12 How does a Neural network work?
Q. 13 Differentiate between Classification and Regression.
Q. 14 Explain the term Resolution.
Q. 15 Differentiate between stemming and lemmatization. Explain with the help
of an example.
Q. 16 What are image features in opencv?
Answer any 3 out of the given 5 questions in 50– 80 words each (4 x 3 = 12 marks)
Q. 17 Discuss Data Sciences, Machine Learning, Computer Vision and NLP with the
help of examples.
Q. 18 Create a 4W Project Canvas for the following.
Although for most people COVID-19 causes only mild illness, it can make some people
very ill. More rarely, the disease can be fatal. Older people, and those with pre- existing
medical conditions such as high blood pressure, heart problems or diabetes appear to
be more vulnerable.
Q. 19 What is Convolutional Neural Network(CNN)? Explain each layer. Q. 20
Differentiate between Supervised and Unsupervised machine learning Models.
Q 21. In schools, a lot of times it happens that there is no water to drink. In a few
places, cases of water shortage in schools are very common and prominent. Hence, an
AI model is designed to predict if there is going to be a water shortage in the school in
near future or not.
The confusion matrix for the same is:
The Confusion Reality : 1 Reality : 0
Matrix
Predicted :1 22 12
Predicted : 0 40 10
Calculate Accuracy, Precision , Recall and F1 Score for this.
