Data & Artificial Intelligence (AI)

Question 1

“Data Literacy” refers to the ability to do what four things with data?

Answer 1

• Read
• Work with
• Analyze
• Argue with

Question 2

What are the “Three Us” (U being “Understand”) of data storytelling?

Answer 2

• Understand the data
• Understand the audience
• Understand the business question or need

Question 3

What data analysis technique “summarizes the main features of a dataset, providing insights into its characteristics”?

Answer 3

Descriptive analysis

Question 4

What data analysis technique “uses a sample dataset to infer conclusions about the larger population of data”?

Answer 4

Inferential analysis

Question 5

What data analysis technique “identifies patterns and relationships in historical data to predict future outcomes, using algorithms and machine learning techniques”?

Answer 5

Predictive analysis

Question 6

What data analysis technique aims to understand the reasons behind past events or outcomes by analyzing historical data to identify causes, often used in troubleshooting and problem-solving.”?

Answer 6

Diagnostic analysis

Question 7

What data analysis technique “recommends actions in order to achieve desired goals”?

Answer 7

Prescriptive analysis

Question 8

What sort of artificial intelligence has the functionality of “[focusing] on one narrow task”?

Answer 8

Artificial Narrow Intelligence (ANI)

Question 9

What sort of artificial intelligence has the functionality of “understanding and learning any intellectual task that a human can”?

Answer 9

Artificial General Intelligence (AGI)

Question 10

What sort of artificial intelligence would have the ability to “surpass human intelligence, evoking emotions, needs, and / or beliefs of its own”? [hypothetically exists]

Answer 10

Artificial Super Intelligence (ASI)

Question 11

Artificial intelligence can be categorized into two categories; what are they?

Answer 11

• Technology: the type of technology the AI uses
• Functionality: what sort of functionality AI uses to complete its tasks

Question 12

What subset of artificial intelligence uses training data and an initial algorithm to predict results and then continuously tests and tweaks the algorithm it uses until acceptable predictions are generated?

Answer 12

Machine learning

Question 13

What subset of artificial intelligence uses neural networks to train itself?

Answer 13

Deep learning

Question 14

What are the three main differences between machine learning and deep learning?

Answer 14

• Deep learning has better performance with similar amounts of data
• Deep learning does not require feature extraction to be done manually by a human
• Deep learning requires much more processing power

Question 15

What branch of artificial intelligence can understand, analyze and interpret text and spoken word in the same way human beings can?

Answer 15

Natural Language Processing (NLP)

Question 16

Why is understanding data sources important in data storytelling?

Answer 16

Being able to explain the data sources used helps build credibility and allows the audience to assess the reliability of the insights presented.

Question 17

What is the role of the scientific method in data science?

Answer 17

Data science applies the scientific method (asking questions, forming hypotheses, testing with data) to make evidence-based decisions and predictions, moving beyond intuition and guesswork.

Question 18

“An interdisciplinary field combining computer science, math and statistics, and domain knowledge to extract insights from data and transform it into actionable knowledge.” is the definition for what?

Answer 18

Data science

Question 19

What are the key roles on a data science team?

Answer 19

Data scientist, data engineer, and subject matter expert. Other roles may include project manager, software developer, and designer.

Question 20

List a couple popular tools used in data science.

Answer 20

• Programming Languages: SQL, Python, R.
• Relational Databases: MySQL, Microsoft SQL Server, PostgreSQL.
• Big Data Platforms: Spark, Hive.
• Spreadsheets/BI Tools: Excel, Tableau.

Question 21

Describe the steps in the data science process.

Answer 21

1. Define the question.
2. Collect data.
3. Prepare data.
4. Create a model.
5. Evaluate the model.
6. Deploy the model.

Question 22

What are the key ingredients of a data-driven organization?

Answer 22

Strategy, people, data, technology, and culture.

Question 23

Describe the data-driven hierarchy of needs.

Answer 23

1. Collect data.
2. Organize data.
3. Analyze data.
4. Make predictions.
5. Automate.

Question 24

What are the three types of AI based on technology?

Answer 24

• Artificial Narrow Intelligence (ANI)
• Artificial General Intelligence (AGI)
• Artificial Super Intelligence (ASI).

Question 25

What are the characteristics of reactive machines in AI?

Answer 25

• Operate solely on current information
• Lacking memory or the ability to learn from past experiences
• React to input and perform programmed tasks.

Question 26

What distinguishes limited memory AI systems?

Answer 26

They can learn from past data and experiences, enabling them to make more informed decisions compared to reactive machines.

Question 27

How does a machine learning algorithm learn?

Answer 27

1. Trained on data
2. Receiving feedback on its predictions
3. Adjusting its parameters to improve accuracy over time.

Question 28

What is a key difference between deep learning and machine learning in feature extraction?

Answer 28

Deep learning automatically learns features from data, while traditional machine learning requires manual feature engineering.

Question 29

What are the two main phases of Natural Language Processing (NLP)?

Answer 29

1. Data preprocessing (preparing text data)
2. Algorithm development (creating rules or models to process the data)

Question 30

Give four examples of data preprocessing techniques in Natural Language Processing (NLP).

Answer 30

• Tokenization (breaking text into smaller units).
• Stop word removal (eliminating common words).
• Lemmatization/stemming (reducing words to their root form).
• Part-of-speech tagging.

Question 31

What are the two main types of Natural Language Processing (NLP) algorithms?

Answer 31

• Rule-based systems (using handcrafted linguistic rules)
• Machine learning-based systems (using statistical models trained on data).