MODEL TEST PAPER (XII AI)

MODEL TEST PAPER – 4

Class – XII                                                                              Subject – Artificial Intelligence
Max. Time: 2 Hours                                                              Max. Marks: 50

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General Instructions:

1. This Question Paper consists of 21 questions divided into two sections: Section A and Section B.
2. Section A contains Objective Type Questions (24 marks), while Section B consists of Subjective Type Questions (26 marks).
3. Out of the given 21 questions, you have to answer 15 questions (5 from Employability Skills and 10 from Subject Specific Skills).
4. All questions in a section must be answered in the correct sequence.

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SECTION A: OBJECTIVE TYPE QUESTIONS

1. Answer any 4 out of the given 6 questions. (1 x 4 = 4 marks)
   (i) Which of the following is not a basic personality trait?
   (a) Emotional stability (b) Extraversion
   (c) Violent (d) Agreeableness
   (ii) What is the meaning of ‘S’ in “SMART” in goal setting?
   (a) Special (b) Simple
   (c) Small (c) Specific
   (iii) In impress, the slide that announces the topic and sets the tone for the presentation is the________.
   (a) Master slide (b) Content slide
   (c) Title slide (d) Handout
   (iv) Which of the following is not a quality of a successful entrepreneur?
   (a) Willingness to take risks (b) Ability to learn
   (c) Motivated (d) Taking frequent holidays
   (v) Which of the following is not an entrepreneurial competency?
   (a) Persistence (b) Commitment
   (c) Aversion to risk (d) Systematic planning
   (vi) In OpenOffice Calc, __ are predefined formula that perform calculations using specific values called arguments.

(a) Expressions
(b) Functions
(c) Filters
(d) Calculations

2. Answer any 5 out of the given 6 questions. (1 x 5 = 5 marks)
   (i) Which of the following is not an AI development tool?
   (a) Keras (b) TensorFlow
   (c) Scikit-Learn (d) C
   (ii) A _____ function determines how well a certain algorithm models the data. (a) Loss (b) Objective (c) Gradient Descent (d) Optimization (iii) Data Storytelling uses narrative elements of characters, setting, conflict and ______ .
   (a) Maps (b) Resolution
   (c) Language (d) Visuals
   (iv) Which of the following depicts the Linear Regression Line Equation (x=independent variable, y= dependent variable, m=slope of line , c= y-intercept)?

(a) y = cx+m
(b) y = mx+c
(c) x = my+c
(d) x = cy+m
(v) State True or False:
K-fold cross-validation is better for small dataset.
(vi) Train-Test Ratio is a_______ and slope of Regression line is a________ .
(a) Parameter, Hyperparameter (b) Classification, Regression
(c) Hyperparameter, Parameter (d) Predictive model, Descriptive model

3. Answer any 5 out of the given 6 questions. (1 x 5 = 5 marks)
   (i) Which of the following is not a Regression Loss?
   (a) Log Loss (b) MSE
   (c) RMSE (d) MAE
   (ii) Assertion (A): Data stories are more interesting and engaging than looking at data.
   Reason (R): Data stories transform a dry collection of facts to something that is more entertaining, thought-provoking and inspirational.
   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 but 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) State True/False:
   Hyperparameter tuning cannot be done by selecting a specific loss function.
   (iv) Data acquisition, data exploration and modelling are part of______ stage of Model Life Cycle.
   (a) Problem Scoping (b) Deployment
   (c) Design (d) Maintenance
   (v) The correct sequence of stages of design thinking is:
   (a) Empathize–Define–Ideate–Prototype–Test
   (b) Empathize–Define–Prototype–Test–Ideate
   (c) Ideate–Define–Prototype–Test–Empathize
   (d) None of these
   (vi) State True/False:
   In K-fold cross-validation, K signifies the number of iterations.
4. Answer any 5 out of the given 6 questions. (1 x 5 = 5 marks)
   (i) It is the average of absolute errors in predicted values.
   (a) MSE (b) MAE
   (c) MBE (d) RMSE
   (ii) Which of the following is a model parameter?
   (a) Coefficients or weights of linear and logistic regression models
   (b) Weights and biases of a neural network
   (c) Cluster centroids in clustering
   (d) All of these
   (iii) Which of the following is one of the Open Frameworks to develop AI applications?
   (a) Python (b) TensorFlow
   (c) JDK (d) .NET
   (iv) State True/False:
   For measuring model quality, a simple train-test split is sufficient for smaller data sets while cross-validation is sufficient for larger dataset.
   (v) Which of the following measures the difference between actual outcome and expected outcome of the target variable?
   (a) Bias (b) Precision
   (c) Mean Absolute Percentage Error (d) None of these

(vi) If the question is to show relationships, then a __ model might be used.

(a) Predictive (b) Descriptive
(c) Diagnostic (d) Prescriptive

5. Answer any 5 out of the given 6 question s (1 x 5 = 5 marks)
   (i) Which of the following is a cross-validation technique?
   (a) K-Fold Cross Validation (b) Holdout Method
   (c) Both (a) and (b) (d) None of these
   (ii) Time Series Decomposition involve the following component.
   (a) Trend (b) Seasonality
   (c) Noise (d) All of the above
   (iii) Which of these is not a parameter?
   (a) Coefficient of Linear regression (b) Weights and Biases in ANN
   (c) Train-Test Ratio (d) None of the above
   (iv) Parameters are to the model because the model can change its values during learning/training.
   (a) External (b) Internal
   (v) State True/False:
   Linear Regression is an example of classification algorithm.
   (vi) _____is not sensitive towards outliers.
   (a) MAE (b) RMSE
   (c) MSE (d) None of the above

SECTION B: SUBJECTIVE TYPE QUESTIONS

Answer any 3 out of the given 5 questions.                                     (2 x 3 = 6 marks)

Answer each question in 20 – 30 words.

6. Write steps how to apply auto-filter in libreoffice Calc.

7. Mention two qualities of an Entrepreneur?

8. Explain briefly Entrepreneurial Competency.

9. Why is self-motivation important?

10. List five-factor model (OCEAN) for personality traits.

Answer any 4 out of the given 6 questions in 20 – 30 words each          (2 x 4 = 8 marks)

11. Explain first two components of Design Thinking.

12. What is MSE? Explain briefly.

13. List the elements of data storytelling.

14. Write Problem Decomposition Steps.

15. Define Training and Testing data.

16. Name all the stages of AI Project Cycle.

Answer any 3 out of the given 5 questions in 50– 80 words each         (4 x 3 = 12 marks)

17. What is Storytelling? Describe “explain, enlighten and engage” with respect to data story.

18. Suppose we would like to build a regression model that uses “hours studied”  as predictor and “exam score” of students as target variable of a particular college entrance exam.

The Regression Line equation is as follows:

Exam Score = 75 + 3*(Hours Studied)

Calculate the RMSE(Root Means Square Error) for the above data.

19. Describe the 10 stages of ‘Foundational Methodology of Data Science’ briefly.

20. Explain the Cross Validation Procedure. In which situation is it better than a Train Test Split?

21. Create a data story with the information given below and use your imagination to reason as to why some cases have spiked while others have seen a fall.