Master AI Fundamentals: Introduction to Artificial Intelligence for MSc Computer Science

Question 1

What does machine learning primarily involve?

Accepted Answer

Enabling computers to learn from data and patterns without explicit instructions

Answer

Manually programming computers to solve specific problems

Answer

Creating intelligent software agents that can reason and make decisions

Answer

Developing computer systems capable of human-like communication

Question 2

Which type of machine learning algorithm learns from labeled data?

Accepted Answer

Supervised learning

Answer

Unsupervised learning

Answer

Reinforcement learning

Answer

Semi-supervised learning

Question 3

Which of the following is a technique used in natural language processing for understanding the structure and meaning of text?

Accepted Answer

Part-of-speech tagging

Answer

Clustering

Answer

Principal component analysis

Answer

Linear regression

Question 4

What is the fundamental distinction between weak AI and strong AI?

Accepted Answer

Weak AI handles well-defined tasks while strong AI possesses general problem-solving capabilities

Answer

Strong AI is more common in research while weak AI is more prevalent in commercial products

Answer

Weak AI emphasizes accuracy while strong AI focuses on efficiency

Answer

There is no substantial difference between weak AI and strong AI

Question 5

What is the primary purpose of the Turing Test?

Accepted Answer

To assess whether a machine can exhibit intelligent behavior indistinguishable from a human

Answer

To measure the accuracy of machine learning models

Answer

To compare the efficiency of natural language processing algorithms

Answer

To evaluate the user experience of virtual assistants

Question 6

Which component of an expert system is responsible for making inferences and solving problems?

Accepted Answer

Inference engine

Answer

Knowledge base

Answer

User interface

Answer

Working memory

Question 7

What is the primary role of heuristic knowledge in Artificial Intelligence?

Accepted Answer

To complement logical reasoning by handling uncertainty and making approximations

Answer

To provide complete and infallible rules for decision-making

Answer

To enhance the speed and efficiency of AI algorithms

Answer

To simplify the development and implementation of AI systems

Question 8

Which of the following is NOT a recognized type of machine learning?

Accepted Answer

Quantum computing

Answer

Supervised learning

Answer

Unsupervised learning

Question 9

Which of the following is NOT a primary subfield of artificial intelligence?

Accepted Answer

Computer graphics

Answer

Machine learning

Answer

Natural language processing

Answer

Computer vision

Question 10

Which machine learning algorithm is commonly used for supervised learning tasks involving classification?

Accepted Answer

Support vector machines

Answer

K-nearest neighbors

Answer

Gaussian mixture models

Answer

Apriori algorithm

Question 11

What is the overarching goal of natural language processing (NLP)?

Accepted Answer

To enable computers to interpret, generate, and manipulate human language.

Answer

To translate programming languages into natural language.

Answer

To analyze the structure and semantics of written text.

Answer

To store and retrieve information from natural language documents.

Question 12

Which technique is commonly employed to represent knowledge within AI systems?

Accepted Answer

Ontologies

Answer

Bayesian networks

Answer

Decision trees

Answer

Hidden Markov models

Question 13

What is the purpose of the Turing test?

Accepted Answer

To evaluate the ability of a computer system to exhibit intelligent behavior indistinguishable from that of a human.

Answer

To measure the computational power of a computer system.

Answer

To train AI systems using natural language processing techniques.

Answer

To design neural network architectures.

Question 14

What is the significance of deep learning in the field of artificial intelligence?

Accepted Answer

It enables the development of AI systems capable of learning complex patterns and representations from data.

Answer

It is a type of machine learning that excels in solving linear regression problems.

Answer

It is primarily used for knowledge representation in AI systems.

Answer

It is a technique specifically designed for natural language processing.

Question 15

Which topic is not covered in the 'Introduction to Artificial Intelligence' unit?

Accepted Answer

Database Management

Answer

Machine Learning

Answer

Natural Language Processing

Question 16

What is the process of training a machine learning model using historical data called?

Accepted Answer

Training

Answer

Inference

Answer

Optimization

Answer

Validation

Question 17

Which of the following techniques is commonly used for feature extraction in Natural Language Processing?

Accepted Answer

Bag of Words

Answer

Convolutional Neural Networks

Answer

Decision Trees

Answer

K-Means Clustering

Question 18

What is the fundamental difference between supervised and unsupervised learning?

Accepted Answer

Supervised learning uses labeled data, while unsupervised learning does not.

Answer

Supervised learning is used for classification, while unsupervised learning is used for regression.

Answer

Supervised learning is more accurate than unsupervised learning.

Answer

Unsupervised learning is more efficient than supervised learning.

Question 19

What is the term for an AI system that learns to optimize its actions based on feedback from its environment?

Accepted Answer

Reinforcement Learning

Answer

Generative Adversarial Network

Answer

Deep Learning

Answer

Transfer Learning

Question 20

What is the term for the ability of an AI system to act in an autonomous manner without human intervention?

Accepted Answer

Autonomy

Answer

Adaptability

Answer

Intelligence

Answer

Learning

Question 21

In machine learning, what is the process of providing a model with labeled data referred to as?

Accepted Answer

Training

Answer

Evaluation

Answer

Optimization

Answer

Deployment

Question 22

Which of the following tasks is commonly associated with natural language processing (NLP)?

Accepted Answer

Sentiment analysis

Answer

Database management

Answer

Image classification

Answer

Numerical forecasting

Question 23

What is the primary distinction between supervised and unsupervised machine learning approaches?

Accepted Answer

Supervised learning utilizes labeled data while unsupervised learning does not.

Answer

Supervised learning is more complex than unsupervised learning.

Answer

Unsupervised learning is more accurate than supervised learning.

Answer

Supervised learning is primarily used for classification while unsupervised learning is used for clustering.

Question 24

What is the purpose of the Turing Test?

Accepted Answer

To determine if a machine can exhibit intelligent behavior indistinguishable from a human

Answer

To measure the accuracy of a machine learning model

Answer

To evaluate the performance of a natural language processing system

Answer

To assess the ethical implications of AI

Question 25

In natural language processing, what does tokenization refer to?

Accepted Answer

Breaking down text into smaller units, such as words or characters

Answer

Identifying grammatical structures within sentences

Answer

Performing sentiment analysis on text

Answer

Generating new text from scratch

Question 26

What is the primary purpose of the backpropagation algorithm in neural networks?

Accepted Answer

Adjusting weights to improve the performance of the network

Answer

Finding the optimal solution to a given problem

Answer

Reducing overfitting to improve generalization

Answer

Improving the accuracy of predictions

Question 27

Which of the following techniques is commonly used for dimensionality reduction in machine learning?

Accepted Answer

Principal component analysis

Answer

Logistic regression

Answer

Support vector machines

Answer

Linear regression

Question 28

What is the fundamental goal of reinforcement learning in AI?

Accepted Answer

Learning from experience through trial and error to optimize behavior

Answer

Generating text or images from scratch

Answer

Classifying data into different categories

Answer

Making predictions based on historical data

Question 29

Which of the following is an example of a deep learning architecture?

Accepted Answer

Convolutional neural network

Answer

Random forest

Answer

Naive Bayes classifier

Answer

Support vector machine

Question 30

What is the purpose of the Turing Test in the field of AI?

Accepted Answer

Assessing the intelligence of machines by testing their ability to exhibit human-like behavior

Answer

Evaluating the performance of NLP models on text generation tasks

Answer

Measuring the accuracy of computer vision algorithms on image recognition tasks

Answer

Testing the efficiency of search engines in retrieving relevant information

Question 31

What is algorithmic bias, and how can it impact the fairness and accuracy of AI decision-making?

Accepted Answer

Algorithmic bias occurs when an AI model is trained on data that doesn't represent the population it's intended for.

Answer

Algorithmic bias is only a concern for AI systems used in high-stakes decisions.

Answer

Increasing the amount of training data for an AI model always eliminates algorithmic bias.

Answer

Algorithmic bias is a minor issue that can be easily identified and fixed.

Question 32

In computer vision, which technique is used to identify and separate objects of interest?

Accepted Answer

Image Segmentation

Answer

Image Classification

Answer

Image Super-Resolution

Answer

Image Denoising

Question 33

For training machines to learn autonomously from unlabeled data, which technique is employed?

Accepted Answer

Unsupervised Learning

Answer

Rule-Based Systems

Answer

Computer Vision

Answer

Knowledge Engineering

Question 34

Within AI, which domain endows machines with the ability to interpret and communicate in natural language?

Accepted Answer

Natural Language Processing

Answer

Data Mining

Answer

Robotics

Answer

Computer Graphics

Question 35

What is the primary objective of supervised learning in AI?

Accepted Answer

Establishing a mapping between input data and corresponding output labels

Answer

Creating synthetic data

Answer

Identifying patterns in unlabeled data

Question 36

Which potential ethical concern arises in the development and deployment of AI systems?

Accepted Answer

Bias and Algorithmic Discrimination

Answer

Excessive Energy Consumption

Answer

Insufficient Computational Resources

Answer

Data Scarcity

Question 37

How does an expert system differ from a knowledge-based system?

Accepted Answer

Expert systems incorporate a reasoning engine, while knowledge-based systems do not.

Answer

Knowledge-based systems are exclusively used for medical diagnostics, while expert systems have broader applications.

Answer

Expert systems are inherently more accurate than knowledge-based systems.

Question 38

What is the primary goal of employing ensemble methods in AI?

Accepted Answer

To enhance the accuracy and robustness of machine learning models

Answer

To address missing data in the training set

Answer

To minimize computational costs associated with training models