Data Science MCQ

The design is the process of using data to find solutions/ to predict the outcomes of a problem statement. 
It is also known as data-driven science and is an interdisciplinary field about scientific methods and processes and systems to extract knowledge or insights from data in various forms structured or unstructured.

There are mainly 5 stages in the data science process:

  • Understanding business problem
  • Data collection
  • Data cleaning and Exploration
  • Model building
  • Collect insights

Artificial intelligence, Machine learning, and Deep learning are a part of Data Science.

Machine learning is the Science of Getting computers to learn without being explicitly programmed.  Machine learning works on a simple concept that is understanding with experiences.

The primary aim of machine learning is to allow computers to learn automatically without human interaction.

Types of machine learning:

  • Supervised learning:
    • in supervised learning, given training explains examples of Input and corresponding output, the machine can predict outputs for new inputs
    • in supervised learning, we train the images concerning data that is well labelled and with the correct output.
  • Unsupervised learning:
    • Unsupervised learning deals with the unlabeled data
    • No training data set is provided which means, no training will be given to the machine. Therefore it must work on its own to discover the required information.
    • The machine is trained with unlabelled data.

Artificial Intelligence is one of the booming fields in the computer science field, which is bringing about a global revolution by making intelligent machines. It is currently all around us in the modern world and is making an entry into every field ranging from playing chess to robotics, to self-driving cars, to proving mathematical theorems.

Artificial Intelligence is made up of 2 words Artificial meaning “Man-Made” and Intelligence meaning “power to think”, making it a “man-made thinking machine”. The end goal of Artificial Intelligence is to make a machine that can think like humans and make decisions based on certain factors. 

Goals of Artificial Intelligence:

The main goals Artificial Intelligence aims to achieve are as follows:

  • Solve knowledge-intensive tasks.
  • Replicate human intelligence to make meaningful decisions.
  • Building a machine that can perform tasks that usually require human intelligence.
  • Build a machine that demonstrates intelligent behaviour and is capable of learning new stuff from past data/experiences.

Data Science MCQ

1. 

Procedural Domain Knowledge in a rule-based system, is in the form of?

Meta-Rules

Control Rules

Production Rules

None of the above
2. 

Identify the clustering method which takes care of variance in data

Decision tree

Gaussian mixture model

K means

All of the above
3. 

Identify the Incorrect CLI command.

clear

rm

delete

None of the above
4. 

Identify the key data science skills among the following

data visualization

machine learning

Statistics

all of the above
5. 

Identify the language which is used in data science?

C++

R

Java

Ruby
6. 

Identify the model which is  usually a gold standard for data analysis

Casual

Inferential

Descriptive

all of the above
7. 

Identify the revision control system on the following.

Scipy

Numpy

Git

Slidify
8. 

Inference engines work on the principle of?

Backward Chaining

Forward Chaining

Both A and B

None of the above
9. 

Knowledge in AI can be represented as?

Predicate Logic

Propositional Logic

Both A and B

None of the above
10. 

Machine learning is a subset of which of the following.

Artificial intelligence

deep learning

data learning

none of the above
11. 

Machines running LISP are also called?

AI Workstations

Time-Sharing Terminals

Both A and B

None of the above
12. 

Out of the given options, which of the following algorithms uses the least memory?

DFS

BFS

Both A and B are the same

Cannot be compared
13. 

PEAS is an abbreviation for?

Peace, Environment, Action, Sense

Peer, Environment, Actuators, Sensors

Performance, Environment, Actuators, Sensors

Performance, Environment, Actuators, Sense
14. 

Identify the activation function output which is zero centered

Hyperbolic tangent

Rectified linear unit

Sigmoid

Softmax
15. 

Raw data should be processed only one time. Is the following statement true or false?

True

False
16. 

The different types of machine learning are?

Supervised

Unsupervised

Reinforcement

All of the above
17. 

Total groups in which data can be characterized is?

1

2

3

4
18. 

Total principles of analytical graphs that exist are __________

2

4

6

8
19. 

Total types of layer in radial basis function neural networks is ______

1

2

3

4
20. 

What are different machine learning methods?

Memorization

Analogy

Deduction

All of the above
21. 

What does K stand for in K mean algorithm?

number of clusters

number of data

number of attributes

Number of iterations
22. 

Which of the following architecture is also known as systolic arrays?

MISD

SISD

SIMD

None of the above
23. 

Which of the following is not a part of the data science process?

communication building

operationalize

model planning

Discovery
24. 

Which of the following is not a supervised learning

PCA

Naive Bayesian

linear regression

Decision tree
25. 

Which of the following machine learning algorithm is based upon the idea of bagging?

decision tree

random-forest

Classification

regression
26. 

Choose the general limitations of the backpropagation rule among the following.

slow convergence

Scaling

local minima problem

All  of the above
27. 

A hybrid Bayesian Network consists of?

Discrete Variables

Continuous Variables

Both A and B

None of the above
28. 

Among the following identify the one in which dimensionality reduction reduces.

Performance

Entropy

Stochastics

collinearity
29. 

Among the following logic function, which of the following cannot be implemented by a  perceptron having two inputs

XOR

NOR

OR

AND
30. 

Among the following options choose which one of the following focuses on the discovery of unknown properties on the data.

Big data

Data mining

Machine learning

Data wrangling
31. 

Among the following options identify the one which is false regarding regression.

it is used for the prediction

it is used for  interpretation

it relates inputs to outputs

it discovers casual relationships
32. 

Among the following SGD  variant, which of the following is based on both Momentum and adaptive learning.

RMSprop

Adam

Nesterov

Adagrad
33. 

Among the following, choose the correct application of data science in Healthcare.

Data science for genomics

Data science for medical imaging

Drug discovery with data science

All of the above
34. 

Another name of data dredging is

Data booting

Data bagging

Data snooping

Data merging
35. 

Another name of data fishing is?

Data merging

Data dredging

Data bagging

None of the above
36. 

Artificial Intelligence is associated with computers of which generation?

Second

First

Fifth

Third
37. 

Choose a disadvantage of decision trees among the following.

Decision trees are robust to outliers

factor analysis

decision trees are prone to overfit

All of the above
38. 

Choose the correct components of data science.

domain expertise

data engineering

advanced computing

all of the above
39. 

A column is a  _________- representation of data.

Diagonal

Vertical

Top

horizontal
40. 

Choose the instance-based learner.

Eager learner

lazy learner

both a and b are correct

none of the above
41. 

Choose whether the following statement is true or false:  Time deltas are differences in times, expressed in difference units

True

False
42. 

Choose whether the following statement is true or false:  Unstructured data is not organized

True

False

maybe true or false

cannot be determined
43. 

Choose whether the following statement is true or false: A data frame is an unstructured representation of data

True

False
44. 

Choose whether the following statement is true or false: Artificial intelligence is the process that allows a computer to learn and make decisions like humans.

True

False
45. 

Choose whether true or false:  Decision tree cannot be used for clustering

True

False
46. 

CLI stands for ___________

Command-line interface

Command language interface

Command-line intercom

None of the above
47. 

Components of an expert system are?

Knowledge base

User interface

Inference engine

All of the above
48. 

FIND-S algorithm ignores?

Positive

Negative

Both

None
49. 

Full form of PAC is _________________

Probably Approx Cost

Probably Approximate Correct

Probability Approx Communication

Probably Approximate Computation
50. 

How many types of observing environments are there?

2

3

0

1
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