Practice Free AIF-C01 Exam Online Questions
A company needs to apply numerical transformations to a set of images to transpose and rotate the images.
- A . Create a deep neural network by using the images as input.
- B . Create an AWS Lambda function to perform the transformations.
- C . Use an Amazon Bedrock large language model (LLM) with a high temperature.
- D . Use AWS Glue Data Quality to make corrections to each image.
An AI company periodically evaluates its systems and processes with the help of independent software vendors (ISVs). The company needs to receive email message notifications when an ISV’s compliance reports become available.
- A . AWS Audit Manager
- B . AWS Artifact
- C . AWS Trusted Advisor
- D . AWS Data Exchange
A company has thousands of customer support interactions per day and wants to analyze these interactions to identify frequently asked questions and develop insights.
Which AWS service can the company use to meet this requirement?
- A . Amazon Lex
- B . Amazon Comprehend
- C . Amazon Transcribe
- D . Amazon Translate
B
Explanation:
Amazon Comprehend is the correct service to analyze customer support interactions and identify frequently asked questions and insights.
Amazon Comprehend:
A natural language processing (NLP) service that uses machine learning to uncover insights and relationships in text.
Capable of extracting key phrases, detecting entities, analyzing sentiment, and identifying topics from text data, making it ideal for analyzing customer support interactions.
Why Option B is Correct:
Text Analysis Capabilities: Can process large volumes of text to identify common topics, phrases, and sentiment, providing valuable insights.
Suitable for Customer Support Analysis: Specifically designed to understand the content and meaning of text, which is key for identifying frequently asked questions.
Why Other Options are Incorrect:
Which technique should be used to fine-tune a pre-trained large language model (LLM) to improve its performance on a specific task?
- A . Zero-shot learning
- B . Few-shot learning
- C . Transfer learning
- D . Unsupervised learning
A hospital is developing an AI system to assist doctors in diagnosing diseases based on patient records and medical images. To comply with regulations, the sensitive patient data must not leave the country the data is located in.
Which data governance strategy will ensure compliance and protect patient privacy?
- A . Data residency
- B . Data quality
- C . Data discoverability
- D . Data enrichment
A healthcare company wants to create a model to improve disease diagnostics by analyzing patient voices. The company has recorded hundreds of patient voices for this project.
The company is currently filtering voice recordings according to duration and language.
- A . Data collection
- B . Data preprocessing
- C . Feature engineering
- D . Model training
A documentary filmmaker wants to reach more viewers. The filmmaker wants to automatically add subtitles and voice-overs in multiple languages to their films.
Which combination of steps will meet these requirements? (Select TWO.)
- A . Use Amazon Transcribe and Amazon Translate to generate subtitles in other languages
- B . Use Amazon Textract and Amazon Translate to generate subtitles in other languages
- C . Use Amazon Polly to generate voice-overs in other languages
- D . Use Amazon Translate to generate voice-overs in other languages
- E . Use Amazon Textract to generate voice-overs in other languages
A, C
Explanation:
The correct answers are A and C because:
Amazon Transcribe converts spoken dialogue from video into text (captions or subtitles).
Amazon Translate translates that transcribed text into other languages.
Amazon Polly can then convert the translated text into lifelike speech for voice-overs in different languages.
From AWS documentation:
"Amazon Transcribe is used to create accurate speech-to-text transcripts. You can feed this text into Amazon Translate to support multilingual subtitles. To generate audio output, Amazon Polly provides neural text-to-speech in multiple languages."
Explanation of other options:
B. Amazon Textract is used for extracting text from documents/images, not audio or video, and is not applicable here.
D. Amazon Translate does not generate speech ― it only translates text.
E. Amazon Textract does not generate audio.
Referenced AWS AI/ML Documents and Study Guides:
Amazon Transcribe Developer Guide C Media Transcription
Amazon Translate Developer Guide C Multilingual Support
Amazon Polly Documentation C Text-to-Speech in Multiple Languages
AWS ML Specialty Guide C Multimedia AI Workflows
A social media company wants to use a large language model (LLM) for content moderation. The company wants to evaluate the LLM outputs for bias and potential discrimination against specific groups or individuals.
Which data source should the company use to evaluate the LLM outputs with the LEAST administrative effort?
- A . User-generated content
- B . Moderation logs
- C . Content moderation guidelines
- D . Benchmark datasets
D
Explanation:
Benchmark datasets are pre-validated datasets specifically designed to evaluate machine learning models for bias, fairness, and potential discrimination. These datasets are the most efficient tool for assessing an LLM’s performance against known standards with minimal administrative effort.
Option D (Correct): "Benchmark datasets": This is the correct answer because using standardized benchmark datasets allows the company to evaluate model outputs for bias with minimal administrative overhead.
Option A: "User-generated content" is incorrect because it is unstructured and would require significant effort to analyze for bias.
Option B: "Moderation logs" is incorrect because they represent historical data and do not provide a standardized basis for evaluating bias.
Option C: "Content moderation guidelines" is incorrect because they provide qualitative criteria rather than a quantitative basis for evaluation.
AWS AI Practitioner
Reference: Evaluating AI Models for Bias on AWS: AWS supports using benchmark datasets to assess model fairness and detect potential bias efficiently.
A company is using custom models in Amazon Bedrock for a generative AI application. The company wants to use a company-managed encryption key to encrypt the model artifacts that the model customization jobs create.
Which AWS service meets these requirements?
- A . AWS Key Management Service (AWS KMS)
- B . Amazon Inspector
- C . Amazon Macie
- D . AWS Secrets Manager
A
Explanation:
AWS KMS provides customer-managed encryption keys (CMKs) that can be used to encrypt model artifacts and other sensitive data at rest.
Bedrock integrates with AWS KMS to allow encryption of customized models with your own keys.
Amazon Inspector is for vulnerability scanning, Amazon Macie for sensitive data discovery, AWS Secrets Manager for storing credentials and secrets.
Reference: AWS Documentation C Using KMS with Amazon Bedrock
A company created an AI voice model that is based on a popular presenter. The company is using the model to create advertisements. However, the presenter did not consent to the use of his voice for the model. The presenter demands that the company stop the advertisements.
Which challenge of working with generative AI does this scenario demonstrate?
- A . Intellectual property (IP) infringement
- B . Lack of transparency
- C . Lack of fairness
- D . Privacy infringement