AWS Certified AI Practitioner AIF-C01 Passing Score

The correct answer is D – Classification. In this scenario, the goal is to assign each social media review to one of three predefined categories: positive, negative, or neutral. According to AWS documentation, classification models are used when “inputs must be mapped to one label from a fixed set of possible labels.” Sentiment analysis is one of the most common NLP classification tasks and is supported in Amazon Comprehend, Amazon SageMaker, and Amazon Bedrock. Open-ended generation produces free-form text and is not appropriate for categorical outputs. Summarization condenses long-form content, and machine translation converts text across languages. Only classification aligns with sentiment detection, enabling the model to learn sentiment cues such as emotional wording or tone markers. AWS highlights sentiment classification as a key use case for supervised learning with text data.

Referenced AWS Documentation:

Amazon Comprehend Documentation – Sentiment Classification

AWS ML Specialty Guide – Classification Algorithms

AWS PrivateLink provides private connectivity between VPCs, AWS services, and on-premises networks, ensuring traffic does not traverse the public internet.

A is correct:

"AWS PrivateLink provides private connectivity to services across VPCs, keeping API traffic off the public internet."

(Reference: AWS PrivateLink Overview)

B (Amazon Q) is a generative AI assistant, not a network security/control tool.

C (CloudFront) is a CDN, not for private API calls.

D (CloudTrail) is for logging and monitoring, not secure connectivity.

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.

Model Accuracy Evaluation:

In image classification, the accuracy of a model is typically evaluated by comparing the predicted labels with the true labels in a benchmark dataset that is representative of the real-world data the model will encounter.

This approach provides a quantifiable measure of how well the model performs on known data and is a standard practice in machine learning.

Why Option B is Correct:

Benchmarking Accuracy: Using a predefined dataset allows for consistent and reliable evaluation of model performance.

Standard Practice: It is a widely accepted method for assessing the effectiveness of image classification models.

Why Other Options are Incorrect:

A. Total cost of resources: Does not measure model accuracy but rather the cost of operation.

C. Number of layers in the neural network: Does not directly correlate with the accuracy or performance of the model.

D. Color accuracy of images processed by the model: Is unrelated to the model’s classification accuracy.

Comprehensive and Detailed Explanation From Exact AWS AI documents:

AWS CloudTrail Lake provides:

Immutable (tamper-proof) storage of API activity

Advanced querying across multiple AWS services

Long-term retention for audit and compliance

AWS governance guidance recommends CloudTrail Lake for centralized, queryable audit logs.

Why the other options are incorrect:

Trusted Advisor (A) gives recommendations.

Macie (B) discovers sensitive data.

Inspector (D) performs vulnerability scans.

AWS AI document references:

AWS CloudTrail Lake Overview

Auditing AI Workloads on AWS

Centralized Compliance Logging