In this article, we share all the MCQ questions for Emerging Trends in Computer Engineering and Information Technology ETI 316313 for computer engineering sixth-semester students.
These questions and answers help students understand all the concepts covered in Chapter One.
These MCQs are as per the new syllabus of computer engineering and information technology.
ETI 316313 Chapter 1 MCQ with Answers
Unit – I Introduction of AI and ML
Artificial Intelligence – Basics
- Artificial Intelligence is mainly concerned with
A) Hardware design
B) Software testing
C) Making machines intelligent
D) Data storage
Ans: C - AI systems are designed to mimic
A) Animal behavior
B) Human intelligence
C) Computer memory
D) Network protocols
Ans: B - Which of the following is the simplest definition of AI?
A) Machines that store data
B) Machines that think and act like humans
C) Machines that follow instructions
D) Machines that run faster
Ans: B - Which capability is NOT part of AI?
A) Learning
B) Reasoning
C) Emotions
D) Problem solving
Ans: C - AI enables machines to learn from
A) Only humans
B) Programs only
C) Data and experience
D) Hardware
Ans: C
Approaches to AI
- Cybernetics is related to
A) Data mining
B) Control systems
C) Databases
D) Networking
Ans: B - Symbolic AI is also known as
A) Weak AI
B) Rule-based AI
C) Neural AI
D) Genetic AI
Ans: B - Symbolic AI mainly uses
A) Images
B) Symbols and rules
C) Sensors
D) Audio signals
Ans: B - Sub-symbolic AI includes
A) Expert systems
B) Neural networks
C) Rule engines
D) Logic programming
Ans: B - Expert systems belong to
A) Symbolic AI
B) Deep Learning
C) Reinforcement Learning
D) Robotics
Ans: A
Components of AI
- Which is NOT a component of AI?
A) Learning
B) Reasoning
C) Perception
D) Formatting
Ans: D - Perception in AI refers to
A) Storing data
B) Sensing environment
C) Programming logic
D) Debugging
Ans: B - Reasoning helps AI systems to
A) Store images
B) Draw conclusions
C) Collect data
D) Display output
Ans: B - Problem solving in AI involves
A) Random guessing
B) Searching solution paths
C) Data storage
D) Memory allocation
Ans: B - Language understanding helps AI to
A) Translate and communicate
B) Store files
C) Compress data
D) Encrypt messages
Ans: A
Types of AI
- Narrow AI is also called
A) Strong AI
B) General AI
C) Weak AI
D) Super AI
Ans: C - Which AI is currently in use?
A) Super AI
B) General AI
C) Narrow AI
D) Human AI
Ans: C - General AI aims to
A) Perform one task
B) Mimic full human intelligence
C) Replace hardware
D) Store big data
Ans: B - Super AI is
A) Already developed
B) Theoretical
C) Used in mobiles
D) Used in banks
Ans: B - AGI stands for
A) Advanced General Intelligence
B) Artificial General Intelligence
C) Automated General Interface
D) Applied General Intelligence
Ans: B
Scope & Applications of AI
- AI is used in healthcare for
A) Cooking
B) Diagnosis
C) Networking
D) Billing only
Ans: B - AI in e-commerce is used for
A) Product recommendations
B) Cable routing
C) Hardware repair
D) Formatting data
Ans: A - AI in finance helps in
A) Fraud detection
B) Painting
C) Music creation only
D) Printing
Ans: A - AI in transportation is used for
A) Manual driving
B) Traffic prediction
C) Fuel selling
D) Road construction
Ans: B - AI scope is
A) Limited
B) Decreasing
C) Expanding
D) Finished
Ans: C
Machine Learning Basics
- Machine Learning is a subset of
A) Networking
B) AI
C) Databases
D) OS
Ans: B - ML enables systems to
A) Be manually programmed
B) Learn from data
C) Stop learning
D) Store only text
Ans: B - Who defined Machine Learning in 1959?
A) Alan Turing
B) John McCarthy
C) Arthur Samuel
D) Marvin Minsky
Ans: C - ML performance improves with
A) Experience
B) Hardware only
C) Memory
D) Speed
Ans: A
Which is NOT a type of ML?
A) Supervised
B) Unsupervised
C) Reinforcement
D) Symbolic
Ans: D
Supervised Learning
- Supervised learning uses
A) Unlabeled data
B) Labeled data
C) No data
D) Random data
Ans: B - Spam detection is an example of
A) Unsupervised learning
B) Reinforcement learning
C) Supervised learning
D) Deep reinforcement
Ans: C - Classification problems use
A) Supervised learning
B) Unsupervised learning
C) Random search
D) Heuristic AI
Ans: A - Regression is used to
A) Classify categories
B) Predict continuous values
C) Cluster data
D) Compress files
Ans: B - Training data in supervised learning contains
A) Only inputs
B) Inputs and outputs
C) Only outputs
D) Noise
Ans: B
Unsupervised Learning
- Unsupervised learning uses
A) Labeled data
B) Unlabeled data
C) Output data
D) Test data only
Ans: B - Clustering is related to
A) Supervised learning
B) Unsupervised learning
C) Reinforcement learning
D) Deep learning only
Ans: B - Market basket analysis uses
A) Reinforcement learning
B) Unsupervised learning
C) Supervised learning
D) Rule-based AI
Ans: B - Unsupervised learning finds
A) Errors
B) Hidden patterns
C) Labels
D) Rules only
Ans: B - k-Means is an example of
A) Supervised algorithm
B) Unsupervised algorithm
C) Reinforcement algorithm
D) Genetic algorithm
Ans: B
Reinforcement Learning
- Reinforcement learning is based on
A) Rules
B) Trial and error
C) Labels
D) Databases
Ans: B - Feedback in reinforcement learning is called
A) Error
B) Loss
C) Reward
D) Label
Ans: C - Reinforcement learning is widely used in
A) Robotics
B) Text editing
C) Printing
D) File storage
Ans: A - An agent interacts with
A) Database
B) Compiler
C) Environment
D) Memory
Ans: C - Gaming AI commonly uses
A) Supervised learning
B) Unsupervised learning
C) Reinforcement learning
D) Symbolic AI
Ans: C
Deep Learning & Neural Networks
- Deep Learning is a subset of
A) AI
B) ML
C) Databases
D) OS
Ans: B - Deep Learning uses
A) Decision trees
B) Neural networks
C) Rule engines
D) Hash tables
Ans: B - A neural network is inspired by
A) CPU
B) Human brain
C) Compiler
D) Memory
Ans: B - Which is NOT a layer in neural networks?
A) Input
B) Hidden
C) Output
D) Control
Ans: D - More hidden layers indicate
A) Shallow network
B) Deep network
C) Weak AI
D) Narrow AI
Ans: B
Generative AI & Transformers
- Generative AI focuses on
A) Prediction
B) Classification
C) Content creation
D) Sorting
Ans: C - Transformers are used mainly in
A) Databases
B) Generative AI
C) Networking
D) OS
Ans: B - Transformers use
A) Backtracking
B) Self-attention
C) Sorting
D) Searching
Ans: B - Self-attention helps model understand
A) Speed
B) Context
C) Memory size
D) Storage
Ans: B - Multi-head attention allows
A) Single focus
B) Parallel attention
C) No attention
D) Manual tuning
Ans: B
AI Security & Ethics
- AI-powered cyber attacks use
A) Human effort only
B) AI techniques
C) Hardware faults
D) Network cables
Ans: B - Adversarial attacks manipulate
A) Hardware
B) Input data
C) Memory
D) Output only
Ans: B - Evasion attacks occur during
A) Training
B) Testing
C) Data collection
D) Deployment planning
Ans: B - Poisoning attacks affect
A) Output only
B) Training data
C) Hardware
D) Software UI
Ans: B
Small input changes that fool AI are called
A) Labels
B) Noise
C) Adversarial examples
D) Rewards
Ans: C
| MCQ Set 1 | Chapter 1 |
| Total MCQ | 100 |
| Download PDF | View |
Conclusion
All the latest chapter one multiple choice questions for engineering students are given above. Students can easily read and start their exam preparations using this MCQ set.