Scribd
Upload
31 views1 page

U22PC402DS

This document is an examination paper for the B.E. IV Semester in Fundamentals of Data Science at MVSR Engineering College, scheduled for August 2024. It includes a compulsory first question and a selection of four additional questions from a total of six, covering various topics such as data science definitions, correlation analysis, data cleaning methods, and different types of regression. Each question is designed to assess knowledge and application of data science concepts, with a total of 70 marks available.

Uploaded by

245123750026
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as PDF, TXT or read online on Scribd
31 views1 page

U22PC402DS

This document is an examination paper for the B.E. IV Semester in Fundamentals of Data Science at MVSR Engineering College, scheduled for August 2024. It includes a compulsory first question and a selection of four additional questions from a total of six, covering various topics such as data science definitions, correlation analysis, data cleaning methods, and different types of regression. Each question is designed to assess knowledge and application of data science concepts, with a total of 70 marks available.

Uploaded by

245123750026
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as PDF, TXT or read online on Scribd
You are on page 1/ 1

R21 Code No.

: U22PC402DS

MATURI VENKATA SUBBA RAO (MVSR) ENGINEERING


COLLEGE(Autonomous)
B.E.IV Semester (Main & Supple.) (Branch: CSE (DS)) Examination, August 2024
FUNDAMENTALS OF DATA SCIENCE
Time : 3 hours Max. Marks : 70
Note : i) FIRST Question is compulsory and answer any FOUR questions from
the remaining six questions. Each question carries 14 Marks.
ii) Answers to each question must be written at one place only and in the same
order as they occur in the question paper.
iii) Missing data, if any, may suitably be assumed.
Q.No. Marks CO BT
1. a) Define Data science? (2) CO1 L1
b) What is correlation analysis? (2) CO2 L1
c) Describe normalization in data analysis? (2) CO3 L2
d) What is Exploratory data analysis? (2) CO4 L1
e) What is linear regression? (2) CO5 L1
f) What is Permutation Test? (2) CO3 L1
g) Describe Regularization? (2) CO5 L2

2 (a) Define Big data? Explain the characteristics of Big data in detail? (7) CO1 L3
(b) Discuss the philosophy of Exploratory data analysis (EDA). (7) CO1 L2
3 (a) Compute Pearson coefficient for the following data: (7) CO2 L3
Cost 39 65 62 90 82 75 25 98 36 78
Sales 47 53 58 86 62 68 60 91 51 84

(b) Discuss the various methods available for data cleaning. (7) CO2 L1
4 (a) Discuss advanced ranking techniques with relevant examples? (7) CO3 L1
(b) Calculate page rank for the below graph (7) CO3 L3

5 (a) What is data visualization? Discuss the different types of data visualizations in (7) CO4 L3
detail.
(b) Explain in brief the evaluation process of models in Data Science. (7) CO4 L3
6 (a) Explain Logistic Regression in detail? (7) CO5 L3
(b) Explain Naive Bayes in detail? (7) CO5 L3
7 (a) Discuss in brief Crowdsourcing? (5) CO2 L2
(b) Use linear regression to estimate slope intercept, RMSE for the following data. (5) CO3 L1
x 1 2 4 3 5
y 1 3 3 2 5
(c) Explain the Supervised Learning with example? (4) CO5 L3
******

You might also like