Free Master of Data Science Questions and Answers

Question 1

Which of the following best sums up data science's main objective?

Accepted Answer

To mine and analyze large amounts of data in order to uncover information that can be used for operational improvements and business gains.

Answer

To collect and prepare data for use as part of analytics applications.

Answer

To collect and archive exhaustive data sets from various source systems for corporate record keeping uses.

Answer

None of the above

Question 2

What phase of the data science process comes first?

Accepted Answer

Defining an analytical hypothesis that could provide business value

Answer

Experimenting with and tuning different analytical models

Answer

Collecting data and preparing it for analysis

Answer

None of the above

Question 3

What distinguishes a data scientist from a data engineer in particular?

Accepted Answer

A data engineer builds data pipelines and helps prepare data, while a data scientist is responsible for data collection, preparation and analysis.

Answer

A data engineer collects and prepares data, and a data scientist then analyzes it.

Answer

A data engineer analyzes data after a data scientist collects and prepares it.

Answer

None of the above

Question 4

False or true? For success, data scientists often need a mix of technical, nontechnical, and the right personality attributes.

Accepted Answer

True

Answer

False

Question 5

Which programming language do data scientists use the most frequently?

Accepted Answer

Python, R and SQL

Answer

Java and JavaScript

Answer

C and C++

Answer

All of the above

Question 6

Which of the following statistical and analytical methods are frequently employed by data scientists?

Accepted Answer

All of the above

Answer

Regression

Answer

Clustering

Answer

Classification

Question 7

What is the main distinction between supervised and unsupervised learning in machine learning?

Accepted Answer

Supervised learning involves data that has been labeled and classified, while unsupervised learning data is unlabeled and unclassified.

Answer

Supervised learning is monitored closely by data scientists, while they don't play a role in unsupervised learning.

Answer

Supervised learning is only used for image recognition, while unsupervised learning can be used for various analytics applications.

Answer

None of the above