A data science team is building a model to predict energy consumption for a smart grid. The dataset includes hourly readings from smart meters, weather data, and holiday calendars. Which data types are present, and what is the primary challenge in combining them?

Image and time-series data; the challenge is processing image data.

Structured and unstructured data; the challenge is extracting features from unstructured text.

Time-series and tabular data; the challenge is aligning different time frequencies and formats.

Labeled and unlabeled data; the challenge is missing labels for weather data.

How does generative AI (GenAI) differ from traditional machine learning?

GenAI is a subset of traditional ML that only works with text data.

Traditional ML is used for regression, while GenAI is used for classification.

Traditional ML requires labeled data, while GenAI does not require any data.

GenAI creates new content, while traditional ML typically makes predictions or classifications.

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Domain 1Objective 1

Task Statement 1.1: Explain Basic AI Concepts and Terminologies. AIF-C01 Practice Questions (Page 4)

Part of the Content Domain 1: Fundamentals of AI and ML domain, which makes up ~20% of our current practice bank. AWS does not publish an official question count, but from its 90-minute exam (~35–60 total, ~7–12 in this domain), expect 2–4 from this objective — we provide 20 practice questions to prepare you well beyond it. (estimate)

20questions here

4free pages

5concepts

Questions 16–20

16expert · hard
A data science team is building a model to predict energy consumption for a smart grid. The dataset includes hourly readings from smart meters, weather data, and holiday calendars. Which data types are present, and what is the primary challenge in combining them?
Select an answer first
17foundation · easy
How does generative AI (GenAI) differ from traditional machine learning?
Select an answer first
18foundation · easy
In the context of AI terminology, what is the process of applying a trained model to new, unseen data to make predictions or generate outputs called?
Select an answer first
19foundation · easy
A company needs to run a model on a large dataset overnight to generate reports for the next morning. Which type of inferencing is most appropriate for this use case?
Select an answer first
20application · medium
A company is developing a system that can recognize objects in images captured by security cameras. The system uses a model that has been trained on millions of labeled images. Which AI subfield does this system belong to?
Select an answer first

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Task Statement 1.1: Explain Basic AI Concepts and Terminologies. AIF-C01 Practice Questions (Page 4)

Questions 16–20

A data science team is building a model to predict energy consumption for a smart grid. The dataset includes hourly readings from smart meters, weather data, and holiday calendars. Which data types are present, and what is the primary challenge in combining them?

How does generative AI (GenAI) differ from traditional machine learning?

In the context of AI terminology, what is the process of applying a trained model to new, unseen data to make predictions or generate outputs called?

A company needs to run a model on a large dataset overnight to generate reports for the next morning. Which type of inferencing is most appropriate for this use case?

A company is developing a system that can recognize objects in images captured by security cameras. The system uses a model that has been trained on millions of labeled images. Which AI subfield does this system belong to?

Keep studying — Content Domain 1: Fundamentals of AI and ML