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Ds Question Paper

This document outlines an examination format for a Data Science course, divided into three parts: Part A consists of 10 short answer questions, Part B includes 5 essay questions, and Part C requires detailed responses to 3 in-depth questions. Topics covered include definitions of key concepts, benefits of data science, machine learning applications, and data retrieval processes. The exam is structured to assess both foundational knowledge and advanced understanding of data science principles and techniques.

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83 views3 pages

Ds Question Paper

This document outlines an examination format for a Data Science course, divided into three parts: Part A consists of 10 short answer questions, Part B includes 5 essay questions, and Part C requires detailed responses to 3 in-depth questions. Topics covered include definitions of key concepts, benefits of data science, machine learning applications, and data retrieval processes. The exam is structured to assess both foundational knowledge and advanced understanding of data science principles and techniques.

Uploaded by

fahmitha778
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
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APRIL 2025 51432/SU45A/SE26B

Maximum: 75 marks
Time: Three hours
PART A -(10x2= 20marks)
in 30 words
Answer any TEN questions each
Define Data Science.

What is Big Data?

Define Distributed File system.

What is data modeling?

What is data preparation?


Define Machine Learning.

7. What is SciPy?
What is Hadoop?
9. What are the core principles of relational
database?

What is NoSQL?
What is data transformation?
What is Elastic Search?
PART B-(5x5= 25 marks)
Answer any FIVEquestions each in 200 words.
What are the benefits and uses of data science?

. What are the main categories of data? Explain.


15.) Write short notes on data exploration.
(16. What are the applications for Machine Learning
in Data science?

17. How does Hadoop achieve parallelism? Explain.


18. Explain different types of NoSQL database.
19) Explain about data retrieval process in data
science.

PART C (3 x 10= 30 marks)

Answer any THREE questions each in 500 words


Explain the Data Science process in detail.
21. Write the overview of techniques to handle
missing data.

2 51432/SU45ASE26B
22. What are the Python tools used in Machine
Learning? Explain in detail.
Explain the process of MapReduce flow with a
neat diagram.
24. Explain about presentation and automation
process in datascience.

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