Data Science Foundations Fundamentals Questions
Graded A+ 2025/2026
People frequently ask whether they should learn python or r to do data science. what is
the answer that this video gives to this question? - A professional data scientist should
be comfortable with both Python and R, as well as several other..... science
While anomaly detection is normally associated with negative outcomes like fraud or
machine failure, it is more flexible than that. which is the following is a positive outcome
in anomaly detection? - Identifying new markets with potential value
What is application programming interface (API)? - API routes the data, translates it,
and prepares it for use
What are artificial nerual networks modeled after? - neurons that are inside a biological
brain
Like general "software-as-a-service" or "saas," what is one of the major attractions of
"machine-learning-as-a-service" or "mlaas"? - You don't need to own or maintain
hardware, which can be flexibly allocated to your project
Which is a major goal of dimensionality reduction? - reducing noise in the data
What is an advantage of in-house data for data science projects? - Certain restrictions
on data usage may not apply
Which is a common application of cluster analysis? - Audience segmentation
How do decision trees provide rules for decision-making? - Decision trees explicitly
define binary decisions at each step in the data to reach the outcome these decisions
can then be used in other contexts
Do human-unaccessible decisions help data science contribute to the interplay of
human and artificial intelligence? - No, because human-inaccessible decisions are not a
way in which data science contributes to the interplay of human and artificial intelligence
How does linear regression provide rules for decision-making? - Linear regression uses
coefficients to combine multiple input variables into a single output variable; these
coefficients can then for decision making
The technique of separating time-series data into an overall trend, a seasonal or cyclical
trend, and random variations or noise is known by which term? - Decomposition
Why have expert systems not progressed as much as machine learning in the
development of decision-making systems? - Expert systems quickly encounter the
Graded A+ 2025/2026
People frequently ask whether they should learn python or r to do data science. what is
the answer that this video gives to this question? - A professional data scientist should
be comfortable with both Python and R, as well as several other..... science
While anomaly detection is normally associated with negative outcomes like fraud or
machine failure, it is more flexible than that. which is the following is a positive outcome
in anomaly detection? - Identifying new markets with potential value
What is application programming interface (API)? - API routes the data, translates it,
and prepares it for use
What are artificial nerual networks modeled after? - neurons that are inside a biological
brain
Like general "software-as-a-service" or "saas," what is one of the major attractions of
"machine-learning-as-a-service" or "mlaas"? - You don't need to own or maintain
hardware, which can be flexibly allocated to your project
Which is a major goal of dimensionality reduction? - reducing noise in the data
What is an advantage of in-house data for data science projects? - Certain restrictions
on data usage may not apply
Which is a common application of cluster analysis? - Audience segmentation
How do decision trees provide rules for decision-making? - Decision trees explicitly
define binary decisions at each step in the data to reach the outcome these decisions
can then be used in other contexts
Do human-unaccessible decisions help data science contribute to the interplay of
human and artificial intelligence? - No, because human-inaccessible decisions are not a
way in which data science contributes to the interplay of human and artificial intelligence
How does linear regression provide rules for decision-making? - Linear regression uses
coefficients to combine multiple input variables into a single output variable; these
coefficients can then for decision making
The technique of separating time-series data into an overall trend, a seasonal or cyclical
trend, and random variations or noise is known by which term? - Decomposition
Why have expert systems not progressed as much as machine learning in the
development of decision-making systems? - Expert systems quickly encounter the
