WGU D429 Introduction to AI for Computer Scientists | Study Guide | Explore New 100
Questions and Answers| 2025 Update|100% Correct.
Section 1: Fundamentals of AI
1. What is Artificial Intelligence (AI)?
o AI refers to the simulation of human intelligence in machines that can learn,
reason, and solve problems.
2. What are the main types of AI?
o Narrow AI (designed for specific tasks) and General AI (which can perform any
intellectual task a human can).
3. What is the difference between AI, Machine Learning (ML), and Deep Learning
(DL)?
o AI is the broader concept of machines mimicking human intelligence, ML is a
subset of AI that enables machines to learn from data, and DL is a subset of ML
that uses neural networks.
4. What are the main components of an AI system?
o Data, algorithms, computing power, and human oversight.
5. Who is considered the father of AI?
o John McCarthy, who coined the term "Artificial Intelligence" in 1956.
6. What is the Turing Test?
o A test proposed by Alan Turing to determine if a machine can exhibit intelligent
behavior indistinguishable from a human.
7. What is an AI agent?
o An AI agent perceives its environment through sensors and acts upon it using
actuators.
8. What are some common real-world applications of AI?
o Virtual assistants (Siri, Alexa), recommendation systems (Netflix, Amazon), self-
driving cars, and medical diagnosis.
9. What is heuristic search in AI?
o A search strategy that uses approximations or rules of thumb to find a solution
efficiently.
10. What is the difference between symbolic AI and connectionist AI?
Symbolic AI uses logic-based rules, while connectionist AI relies on neural networks to
learn patterns.
Section 2: Machine Learning
11. What is supervised learning?
A type of ML where the model is trained on labeled data.
12. What is unsupervised learning?
, A type of ML where the model identifies patterns in unlabeled data.
13. What is reinforcement learning?
A learning method where an agent learns by interacting with an environment and
receiving rewards or penalties.
14. What is overfitting in ML?
When a model learns the training data too well, including noise, leading to poor
generalization.
15. What is underfitting in ML?
When a model is too simple to capture the underlying patterns in data.
16. What is a training dataset?
A dataset used to teach an ML model by adjusting its parameters.
17. What is a validation dataset?
A dataset used to fine-tune model parameters and prevent overfitting.
18. What is a test dataset?
A dataset used to evaluate the final performance of a trained ML model.
19. What is feature engineering?
The process of selecting, transforming, and creating input variables for an ML model.
20. What is cross-validation?
A technique used to assess how well an ML model generalizes to new data.
Section 3: Neural Networks and Deep Learning
21. What is a neural network?
A computational model inspired by the structure of the human brain, consisting of layers
of neurons.
22. What are the three types of layers in a neural network?
Questions and Answers| 2025 Update|100% Correct.
Section 1: Fundamentals of AI
1. What is Artificial Intelligence (AI)?
o AI refers to the simulation of human intelligence in machines that can learn,
reason, and solve problems.
2. What are the main types of AI?
o Narrow AI (designed for specific tasks) and General AI (which can perform any
intellectual task a human can).
3. What is the difference between AI, Machine Learning (ML), and Deep Learning
(DL)?
o AI is the broader concept of machines mimicking human intelligence, ML is a
subset of AI that enables machines to learn from data, and DL is a subset of ML
that uses neural networks.
4. What are the main components of an AI system?
o Data, algorithms, computing power, and human oversight.
5. Who is considered the father of AI?
o John McCarthy, who coined the term "Artificial Intelligence" in 1956.
6. What is the Turing Test?
o A test proposed by Alan Turing to determine if a machine can exhibit intelligent
behavior indistinguishable from a human.
7. What is an AI agent?
o An AI agent perceives its environment through sensors and acts upon it using
actuators.
8. What are some common real-world applications of AI?
o Virtual assistants (Siri, Alexa), recommendation systems (Netflix, Amazon), self-
driving cars, and medical diagnosis.
9. What is heuristic search in AI?
o A search strategy that uses approximations or rules of thumb to find a solution
efficiently.
10. What is the difference between symbolic AI and connectionist AI?
Symbolic AI uses logic-based rules, while connectionist AI relies on neural networks to
learn patterns.
Section 2: Machine Learning
11. What is supervised learning?
A type of ML where the model is trained on labeled data.
12. What is unsupervised learning?
, A type of ML where the model identifies patterns in unlabeled data.
13. What is reinforcement learning?
A learning method where an agent learns by interacting with an environment and
receiving rewards or penalties.
14. What is overfitting in ML?
When a model learns the training data too well, including noise, leading to poor
generalization.
15. What is underfitting in ML?
When a model is too simple to capture the underlying patterns in data.
16. What is a training dataset?
A dataset used to teach an ML model by adjusting its parameters.
17. What is a validation dataset?
A dataset used to fine-tune model parameters and prevent overfitting.
18. What is a test dataset?
A dataset used to evaluate the final performance of a trained ML model.
19. What is feature engineering?
The process of selecting, transforming, and creating input variables for an ML model.
20. What is cross-validation?
A technique used to assess how well an ML model generalizes to new data.
Section 3: Neural Networks and Deep Learning
21. What is a neural network?
A computational model inspired by the structure of the human brain, consisting of layers
of neurons.
22. What are the three types of layers in a neural network?
