This document outlines an internal assessment exam for an Introduction to Data Science course. It contains three parts: Part A has 7 short answer questions worth 2 marks each, Part B has 4 longer answer questions worth 5 marks each, and Part C has 2 extended response questions worth 10 marks each. The questions cover topics like defining data science, describing big data and NoSQL databases, uses of scikit-learn in Python, data cleansing, outliers, dummy variables, benefits of data science and big data, types of data errors, data transformation, exploratory data analysis, presentation and automation, facets of data, the data science process, and data modeling steps. The exam is worth a total of 50 marks and takes 2 hours to complete.

1. Vivekananda Vision Arts and Science College
Department of Computer Science/Applications
Kachur, Uthukottai,Thiruvallur -602026
Continuous Internal Assessment-I - January- 2024
Class : III B.Sc C.S Max. Marks: 50 Time: 2.00 Hrs
Subject: Introduction to Data Science Code: SE26B
PART –A
ANSWER ANY FIVE QUESTIONS 5 x2=10
1. Define data science.
2. What is big data?
3. What is NoSQL database?
4. What is the use of Scikit-learn in python?
5. Define data cleansing.
6. What is an outlier?
7. What is dummy variable?
PART –B
ANSWER ANY FOUR QUESTIONS 4x5=20
8. Explain the benefits and uses of data science and big data
9. List and explain different types of errors found in data
10. Write a short note on data transformation.
11. How exploratory data analysis performed?
12. Write a short note on presentation and automation
PART –C
ANSWER ANY TWO QUESTIONS 2x10=20
13. List and explain different facets of data.
14. Explain data science process.
15. Explain data modelling steps in data science process.
Subject in Charge Principal
Vivekananda Vision Arts and Science College
Department of Computer Science/Applications
Kachur, Uthukottai,Thiruvallur -602026
Continuous Internal Assessment-I - January- 2024
Class : III B.Sc C.S Max. Marks: 50 Time: 2.00 Hrs
Subject: Introduction to Data Science Code: SE26B
PART –A
ANSWER ANY FIVE QUESTIONS 5 x2=10
1. Define data science.
2. What is big data?
3. What is NoSQL database?
4. What is the use of Scikit-learn in python?
5. Define data cleansing.
6. What is an outlier?
7. What is dummy variable?
PART –B
ANSWER ANY FOUR QUESTIONS 4x5=20
8. Explain the benefits and uses of data science and big data
9. List and explain different types of errors found in data
10. Write a short note on data transformation.
11. How exploratory data analysis performed?
12. Write a short note on presentation and automation
PART –C
ANSWER ANY TWO QUESTIONS 2x10=20
13. List and explain different facets of data.
14. Explain data science process.
15. Explain data modelling steps in data science process.
Subject in Charge Principal