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RC on Data Scence and Quantum Computing - Test

Total questions: 20

Worksheet time: 10mins

Name
Class
Date
1.

What is the fundamental unit of quantum information?

a)

Byte

b)

Bit

c)

Qubit

d)

Quantum gate

2.

In quantum computing, superposition refers to:

a)

The ability to be in multiple states at once

b)

The ability to teleport information

c)

The process of measuring quantum states

d)

The destruction of quantum information

3.

Which of the following gates is unique to quantum computing?

a)

XOR gate

b)

NAND gate

c)

Hadamard gate

d)

OR gate

4.

Quantum entanglement means:

a)

Two qubits are isolated from each other

b)

One qubit is in a superposition state

c)

Two qubits are correlated such that the state of one depends on the state of the other, regardless of distance

d)

Qubits randomly change their state

5.

In quantum mechanics, Heisenberg's Uncertainty Principle states that:

a)

We cannot simultaneously know both the energy and time of a quantum system

b)

We can measure both position and momentum exactly at the same time

c)

We can never know anything about quantum systems

d)

Qubits can only exist in a single state at any given time

6.

Which of the following is a major challenge in building quantum computers?

a)

Power consumption

b)

Speed of computation

c)

Quantum decoherence

d)

Large memory requirements

7.

The famous algorithm proposed by Peter Shor in quantum computing is used for:

a)

Factoring large integers

b)

Sorting large datasets

c)

Searching unsorted databases

d)

Solving linear equations

8.

Grover's algorithm provides a quadratic speedup for which type of problem?

a)

Factoring large numbers

b)

Simulating quantum systems

c)

Database search

d)

Matrix inversion

9.

What is the primary difference between classical bits and qubits?

a)

Bits can represent 1 or 0, while qubits can represent both 1 and 0 simultaneously

b)

Bits can exist in superposition, while qubits cannot

c)

Bits are based on quantum mechanics, while qubits are not

d)

There is no difference between bits and qubits

10.

In quantum computing, a "quantum gate" is:

a)

A physical door leading to a quantum lab

b)

An operator that performs a specific operation on qubits

c)

A classical computing instruction set

d)

The output state of a quantum computer

11.

In data science, which of the following is the first step in any data analysis process?

a)

Data visualization

b)

Data cleaning

c)

Data modeling

d)

Data collection

12.

Which of the following is an example of supervised learning?

a)

K-means clustering

b)

Principal Component Analysis (PCA)

c)

Linear regression

d)

Apriori algorithm

13.

In a dataset, which of the following techniques is commonly used to handle missing data?

a)

Data duplication

b)

Mean imputation

c)

Adding noise

d)

Random sampling

14.

In data science, which of the following algorithms is used for classification tasks?

a)

K-means clustering

b)

Decision tree

c)

Principal Component Analysis (PCA)

d)

Linear regression

15.

In which of the following applications is "time series analysis" commonly used?

a)

Recommender systems

b)

Financial forecasting

c)

Image classification

d)

Clustering

16.

In a neural network, what does the "activation function" do?

a)

Initializes the weights

b)

Combines input features

c)

Decides whether a neuron should be activated or not based on input

d)

Normalizes the output

17.

What is the function of the "loss function" in a neural network?

a)

To compute the difference between predicted and actual output

b)

To decide the activation of a neuron

c)

To initialize weights

d)

To adjust the learning rate dynamically

18.

In a convolutional neural network (CNN), what does the "convolution" operation do?

a)

Reduces the dimensionality of the input

b)

Applies filters to the input data to extract features

c)

Combines neurons

d)

Increases the complexity of the model

19.

Which of the following is a type of neural network that is often used for sequential data, such as time series or natural language?

a)

Feedforward Neural Network (FNN)

b)

Convolutional Neural Network (CNN)

c)

Recurrent Neural Network (RNN)

d)

Generative Adversarial Network (GAN)

20.

In a neural network, what is the role of the "optimizer"?

a)

To select the best model architecture

b)

To minimize the loss function by adjusting the weights of the network

c)

To increase the number of neurons in the hidden layers

d)

To perform feature scaling on input data