AI Fundamentals and Concepts

Question 1

What is Artificial Intelligence (AI)?

Answer 1

AI is the ability of machines to think and act intelligently, like a human would.

Question 2

How does AI differ from traditional programming?

Answer 2

AI learns from data and makes decisions, while traditional programming involves telling a computer exactly what to do.

Question 3

What are key areas of AI?

Answer 3

• Computer Vision
• Machine Learning (ML)
• Deep Learning (DL)
• Data Mining

Question 4

What is Weak AI?

Answer 4

AI built for specific tasks—it doesn’t think like a human.

Question 5

Give examples of Weak AI.

Answer 5

• Siri and Alexa
• Chess-playing AI
• Chatbots like GPT-4

Question 6

What is Strong AI?

Answer 6

AI that can think, learn, and adapt like a human.

Question 7

Does Strong AI exist?

Answer 7

Not yet! Scientists are still trying to create it.

Question 8

What is Machine Learning (ML)?

Answer 8

A method where AI is trained on data instead of being programmed manually.

Question 9

What are the two main types of Machine Learning?

Answer 9

• Supervised Learning
• Unsupervised Learning

Question 10

What is Supervised Learning?

Answer 10

The AI is trained on labeled data (data with answers).

Question 11

What is an example of Supervised Learning?

Answer 11

Teaching AI to recognize cats using labeled cat pictures.

Question 12

What is Unsupervised Learning?

Answer 12

AI finds patterns in data by itself—no labels.

Question 13

What is the difference between Machine Learning and Data Mining?

Answer 13

ML = AI learns patterns and makes predictions; Data Mining = Humans find patterns manually in big data.

Question 14

What is Deep Learning (DL)?

Answer 14

A special kind of Machine Learning that uses neural networks.

Question 15

What are key models in Deep Learning?

Answer 15

• CNNs (Convolutional Neural Networks)
• RNNs (Recurrent Neural Networks)
• Autoencoders

Question 16

What is CNN best for?

Answer 16

Images.

Question 17

What is RNN best for?

Answer 17

Sequences like speech and text.

Question 18

Where is AI used?

Answer 18

• Computer Vision
• Natural Language Processing (NLP)
• Generative AI

Question 19

What is an application of AI in Computer Vision?

Answer 19

Medical imaging for detecting diseases from scans.

Question 20

What does Natural Language Processing (NLP) enable AI to do?

Answer 20

Understand language.

Question 21

What is an example of Generative AI?

Answer 21

GANs (Generative Adversarial Networks) that create new images, videos, and music.

Question 22

Fill in the blank: AI is __________ technology that mimics human intelligence.

Answer 22

[smart]

Question 23

True or False: Deep Learning makes AI less powerful than traditional Machine Learning.

Answer 23

False.

Question 24

What are the goals of data exploration?

Answer 24

• Visualize patterns and trends
• Summarize key statistics
• Detect anomalies
• Understand relationships between variables

Question 25

Why is data visualization important?

Answer 25

* Find patterns and trends * Understand relationships between variables * Detect errors or missing data * Make data easier to interpret

Question 26

What types of charts are used for different purposes?

Answer 26

* Relationship → Scatter plots * Composition → Pie charts * Comparison → Bar charts, line graphs * Location → Maps & heatmaps

Question 27

What did researchers Cleveland & McGill find about chart design?

Answer 27

* Position & length are the most accurate ways to show numbers * Pie charts are harder to interpret than bar charts

Question 28

What is the Grammar of Graphics?

Answer 28

* A structured approach to designing visualizations * Ensures consistency in designing graphs * Used in tools like ggplot2 in R

Question 29

What are common data issues in data pre-processing?

Answer 29

* Missing Values * Duplicates * Inconsistent Data * Noise & Outliers

Question 30

What is feature engineering in data pre-processing?

Answer 30

* Feature Selection → Keep important variables * Feature Transformation → Convert data into better formats

Question 31

Fill in the blank: The package used for creating visualizations in R is _______.

Answer 31

[ggplot2]

Question 32

What is the purpose of a scatter plot in data visualization?

Answer 32

Helps us see the relationship between two variables.

Question 33

True or False: Cleaning data is essential for accuracy.

Answer 33

True.

Question 34

What are the key takeaways from the data exploration and visualization process?

Answer 34

* Data exploration helps us understand patterns * Visualization is key for discovering insights * Choosing the right chart aids interpretation * The Grammar of Graphics helps create structured visualizations * Cleaning data is essential for accuracy

Question 35

When do we use Machine Learning?

Answer 35

When no direct formula exists to solve a problem and when we have data that can help find patterns.