AIF-C01 Online Practice Questions and Answers

Correct Answer: A

Decision trees are an interpretable machine learning algorithm that clearly documents the decision-making process by showing how each input feature affects the output. This transparency is particularly useful when explaining how the model

arrives at a certain decision, making it suitable for classifying genes into categories. Option A (Correct): "Decision trees":This is the correct answer because decision trees provide a clear and interpretable representation of how input features

influence the model's output, making it ideal for understanding the inner mechanisms affecting predictions.

Option B:"Linear regression" is incorrect because it is used for regression tasks, not classification.

Option C:"Logistic regression" is incorrect as it does not provide the same level of interpretability in documenting decision-making processes. Option D:"Neural networks" is incorrect because they are often considered "black boxes" and do not

easily explain how they arrive at their outputs.

AWS AI Practitioner References:

Interpretable Machine Learning Models on AWS:AWS supports using interpretable models, such as decision trees, for tasks that require clear documentation of how input data affects output decisions.

Correct Answer: A

Amazon Textract is a service that automatically extracts text and data from scanned documents, including PDFs. It is the best choice for converting resumes from PDF format to plain text for further processing.

Correct Answer: B

Measuring the model's accuracy against a predefined benchmark dataset is the correct strategy to evaluate the accuracy of a foundation model (FM) used in image classification tasks.

Correct Answer: B

Amazon Comprehend is the correct service to analyze customer support interactions and identify frequently asked questions and insights.

Correct Answer: A

A multi-modal embedding model is the correct type of foundation model (FM) for powering a search application that handles queries containing both text and images.

Correct Answer: B

To determine which model generates responses in a style that the company's employees prefer, the best approach is to use a human workforce to evaluate the models with custom prompt datasets. This method allows for subjective

evaluation based on the specific stylistic preferences of the company's employees, which cannot be effectively assessed through automated methods or pre-built datasets. Option B (Correct): "Evaluate the models by using a human workforce

and custom prompt datasets":This is the correct answer as it directly involves human judgment to evaluate the style and quality of the responses, aligning with employee preferences.

Option A:"Evaluate the models by using built-in prompt datasets" is incorrect because built-in datasets may not capture the company's specific stylistic requirements.

Option C:"Use public model leaderboards to identify the model" is incorrect as leaderboards typically measure model performance on standard benchmarks, not on stylistic preferences.

Option D:"Use the model InvocationLatency runtime metrics in Amazon CloudWatch" is incorrect because latency metrics do not provide any information about the style of the model's responses.

AWS AI Practitioner

References:

Model Evaluation Techniques on AWS:AWS suggests using human evaluators to assess qualitative aspects of model outputs, such as style and tone, to ensure alignment with organizational preferences

Correct Answer: D

AWS Data Exchange is a service that allows companies to securely exchange data with third parties, such as independent software vendors (ISVs). AWS Data Exchange can be configured to provide notifications, including email notifications,

when new datasets or compliance reports become available.

Option D (Correct): "AWS Data Exchange":This is the correct answer because it enables the company to receive notifications, including email messages, when ISVs' compliance reports are available.

Option A:"AWS Audit Manager" is incorrect because it focuses on assessing an organization's own compliance, not receiving third-party compliance reports. Option B:"AWS Artifact" is incorrect as it provides access to AWS's compliance

reports, not ISVs'.

Option C:"AWS Trusted Advisor" is incorrect as it offers optimization and best practices guidance, not compliance report notifications.

AWS AI Practitioner

References:

AWS Data Exchange Documentation:AWS explains how Data Exchange allows organizations to subscribe to third-party data and receive notifications when updates are available.

Correct Answer: C

The problem involves a simple probability calculation that can be handled efficiently by straightforward mathematical rules and computations. Using machine learning techniques would introduce unnecessary complexity and operational overhead. Option C (Correct): "Use code that will calculate probability by using simple rules and computations":This is the correct answer because it directly solves the problem with minimal overhead, using basic probability rules. Option A:"Use supervised learning to create a regression model" is incorrect as it overcomplicates the solution for a simple probability problem. Option B:"Use reinforcement learning to train a model" is incorrect because reinforcement learning is not needed for a simple probability calculation. Option D:"Use unsupervised learning to create a model" is incorrect as unsupervised learning is not applicable to this task. AWS AI Practitioner References: Choosing the Right Solution for AI Tasks:AWS recommends using the simplest and most efficient approach to solve a given problem, avoiding unnecessary machine learning techniques for straightforward tasks.

Correct Answer: A

Batch transform in Amazon SageMaker is designed for offline processing of large datasets. It is ideal for scenarios where immediate predictions are not required, and the inference can be done on large datasets that are multiple gigabytes in

size. This method processes data in batches, making it suitable for analyzing archived data without the need for real- time access to predictions.

Option A (Correct): "Batch transform":This is the correct answer because batch transform is optimized for handling large datasets and is suitable when immediate access to predictions is not required.

Option B:"Real-time inference" is incorrect because it is used for low-latency, real- time prediction needs, which is not required in this case. Option C:"Serverless inference" is incorrect because it is designed for small-scale, intermittent

inference requests, not for large batch processing. Option D:"Asynchronous inference" is incorrect because it is used when immediate predictions are required, but with high throughput, whereas batch transform is more suitable for very large

datasets.

AWS AI Practitioner

References:

Batch Transform on AWS SageMaker:AWS recommends using batch transform for large datasets when real-time processing is not needed, ensuring cost- effectiveness and scalability.

Correct Answer: A

Amazon Bedrock offers an on-demand pricing model that provides flexibility without long- term commitments. This model allows companies to pay only for the resources they use, which is ideal for a limited budget and offers flexibility. Option

A (Correct): "On-Demand":This is the correct answer because on-demand pricing allows the company to use Amazon Bedrock without any long-term commitments and to manage costs according to their budget. Option B:"Model

customization" is a feature, not a pricing model. Option C:"Provisioned Throughput" involves reserving capacity ahead of time, which might not offer the desired flexibility and could lead to higher costs if the capacity is not fully used.

Option D:"Spot Instance" is a pricing model for EC2 instances and does not apply to Amazon Bedrock.

AWS AI Practitioner

References:

AWS Pricing Models for Flexibility:On-demand pricing is a key AWS model for services that require flexibility and no long-term commitment, ensuring cost- effectiveness for projects with variable usage patterns.