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Artificial Intelligence Mid-Term Examination for Class XII, Schemes and Mind Maps of Computer science

Computer science

Artificial intelligence. Sample papers 101

Typology: Schemes and Mind Maps

2022/2023

Uploaded on 02/20/2023

madhavan-s-2
madhavan-s-2 🇮🇳

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bg1
XII
)
1
S D Vidya Mandir, HUDA, Panipat
Mid Term Examination, Sep. 2021
Artificial Intelligence
XII
Set-A
Time : 1𝟏
𝟐 Hrs. MM : 25
General Instructions:
1.
Please read the instructions carefully
2.
This Question Paper is divided into 03 sections, viz., Section A, Section B and Section C.
3.
Section A is of 05 marks and has 06 questions on Employability Skills.
4.
Section B is of 15 marks and has 20 questions on Subject Specific Skills.
5.
Section C is of 05 marks and has 07 Situation/ Case/ Data-based questions.
6.
Do as per the instructions given in the respective sections.
7.
Marks allotted are mentioned against each section/question.
8.
All questions must be attempted in the correct order
SECTION- A
Answer any 5 questions out of the given 6 questions on Employability Skills (1 x 5 = 5 marks)
1.
Jason is a Property Agent who provides advice, support and guidance to his
clients’. Jason is able to engage well to his client, there are couple of times
where he tends to ask the next question too quickly before allowing his client
to complete her sentences. And there are few occasions where Jason has to
make his client repeats again in order to understand what the client wants due
to his earlier interruption. eventually, his client started to behave in a more
defensive manner and looking really unhappy. On which feature of Active
listening he needs to work to satisfy his client.
a) Eye contact
b) Pay attention
c) Tune himself to the timing of speaker
d) Empathize
1
2.
Identify the object, verb and subject in the sentence, ‘The car crashed into a tree.’
a) Object: a tree; Verb: crashed; Subject: the car
b) Object: The car; Verb: crashed; Subject: a tree
c) Object: crashed; Verb: the tree; Subject: the car
d) Object: crashed; Verb: the car; Subject: the tree
1
3.
Statement 1: A realistic goal is one that has no timeline or plans for execution.
Statement 2: Breaking down big goals into smaller parts will make the goal
achievable.
a) Both Statement I and Statement II are correct
b) Both Statement I and Statement Il are incorrect
c) Statement I is correct but Statement II is incorrect
d) Statement I is incorrect but Statement II is correct
1
pf3
pf4
pf5

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XII 1

S D Vidya Mandir, HUDA, Panipat

Mid Term Examination, Sep. 2021

Artificial Intelligence

XII

Set-A

Time : 1

𝟏 𝟐

Hrs. MM : 25

General Instructions:

1. Please read the instructions carefully 2. This Question Paper is divided into 03 sections, viz., Section A, Section B and Section C. 3. Section A is of 05 marks and has 06 questions on Employability Skills. 4. Section B is of 15 marks and has 20 questions on Subject Specific Skills. 5. Section C is of 05 marks and has 07 Situation/ Case/ Data-based questions. 6. Do as per the instructions given in the respective sections. 7. Marks allotted are mentioned against each section/question. 8. All questions must be attempted in the correct order

SECTION- A

Answer any 5 questions out of the given 6 questions on Employability Skills (1 x 5 = 5 marks)

  1. Jason is a Property Agent who provides advice, support and guidance to his clients’. Jason is able to engage well to his client, there are couple of times where he tends to ask the next question too quickly before allowing his client to complete her sentences. And there are few occasions where Jason has to make his client repeats again in order to understand what the client wants due to his earlier interruption. eventually, his client started to behave in a more defensive manner and looking really unhappy. On which feature of Active listening he needs to work to satisfy his client. a) Eye contact b) Pay attention c) Tune himself to the timing of speaker d) Empathize
  1. Identify^ the^ object,^ verb^ and^ subject^ in^ the^ sentence,^ ‘The car^ crashed^ into^ a^ tree.’ a) Object: a tree; Verb: crashed; Subject: the car b) Object: The car; Verb: crashed; Subject: a tree c) Object: crashed; Verb: the tree; Subject: the car d) Object: crashed; Verb: the car; Subject: the tree
  1. Statement 1: A realistic goal is one that has no timeline or plans for execution. Statement 2: Breaking down big goals into smaller parts will make the goal achievable. a) Both Statement I and Statement II are correct b) Both Statement I and Statement Il are incorrect c) Statement I is correct but Statement II is incorrect d) Statement I is incorrect but Statement II is correct

XII 2

  1. There was a young boy who was fond^ of playing football and wanted to become a football player. He joined a football academy and came regularly to practice but never made it to the team. For four days, the boy didn’t show up for practice. The matches had begun and his team was playing the finals. He showed up for the finals. He went up to the coach and pleaded him to let him play for the match. The coach had never seen the boy plead like this before. The Game started and the boy played like a ball on fire. Every time he got the ball, he shot a goal. Needless to say, he was the star of the game and his team won. What type of motivation did the boy demonstrate? a) External b) Internal c) Both internal and external d) Not any specific type of motivation
  2. 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.
  1. You have a summer vacation project on how to make biogas. You have done a lot of research, clicked pictures of biogas plants and taken videos of people, who use biogas. Now, you have to make a presentation before the class. What would you use? a) Chart paper b) Word document c) Presentation software d) Spreadsheet

SECTION B

Answer any 15 questions out of the given 20 questions (1 x 15 = 15 marks)

  1. Which^ of^ the^ following^ is^ correct^ about^ the^ rule^ based approach? a) We cannot provide enough rules to the machine. b) A drawback/feature for this approach is that the learning is static. c) Once the rules are fed into the system, it takes into consideration any changes made in the original training dataset. d) It can improve itself based on the feedbacks.
  1. You would interview people to gain an understanding of how they feel during the ____ stage of Design Thinking a) Prototype b) Define c) Ideate d) Empathize

XII 4

  1. (^) How do you handle missing or corrupted data in a dataset? a) Drop missing rows or columns b) Replace missing values with mean/median/mode c) Assign a unique category to missing values d) All of above
  2. A machine learning^ technique that helps in detecting the outliers in data. a) Clustering b) Classification c) Anomaly detection d) All of above
  1. Given 80% of data is selected for training and remaining 20% for testing, and this process is carried out for four times and error rate is averaged out, this validation technique can be called as _______ a) Hold-out b) K-fold cross-validation c) LOOCV d) Bootstrapping
  1. During which stage would you: Start looking for alternative ways of viewing the problem. a) Prototype b) Define c) Ideate d) Empathize
  1. What is model evaluation is used for? a) Assessing the model after getting deployed. b) Assessing the model before getting deployed c) Determining if mode is good for other users. d) All of the above
  1. 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

XII 5

  1. 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)
  2. Select the correct statement. a) The first stage of Data science methodology is data understanding. b) The first stage of Data science methodology is data modeling. c) The first stage of Data science methodology is business understanding. d) The first stage of Data science methodology is data Collection.

Artificial Intelligence is about_____. a) Playing a game on Computer b) Making a machine Intelligent c) Programming on Machine with your Own Intelligence d) Putting your intelligence in Machine

  1. 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
  1. Choose^ the^ correct^ option a) Unsupervised learning - >labelled dataset, Regression b) Supervised learning - > labelled data set, Regression c) Unsupervised learning - >unlabelled dataset, Classification d) Supervised learning - > unlabelled data set, Regression
  1. Google Translate is Google's free service that instantly translates^ words, phrases, and web pages between English and over 100 other languages. Google translate uses ----- a) 4w problem canvas b) Neural Networks c) KWLH chart d) System maps

XII 7

Consider the following data where one input(X) and one output(Y) is given What would be the root mean square training error for this data if you run a Linear Regression model of the form (Y = A0+A1X)? a) Less than 0 b) Greater than 0 c) Equal to 0 d) None of these

  1. Statement:1 At the same time, we^ should keep in mind that the data which we collect is open-sourced and not someone’s property. Statement 2: Extracting private data can be an offence. a) Statement 1 is True b) Statement 2 is True c) Both Statement 1 and 2 are True d) None of these statements are True
  1. Amazon had been working on a secret AI recruiting tool. The machine-learning specialists uncovered a big problem: their new recruiting engine did not like women. The system taught itself that male candidates were preferable. It penalized resumes that included the word “women". This led to the failure of the tool. This is an example of a) Data Privacy b) AI access c) AI Bias d) Data Exploration