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Amazon AIF-C01 Exam Syllabus Topics:
Topic
Details
Topic 1
- Applications of Foundation Models: This domain examines how foundation models, like large language models, are used in practical applications. It is designed for those who need to understand the real-world implementation of these models, including solution architects and data engineers who work with AI technologies to solve complex problems.
Topic 2
- Security, Compliance, and Governance for AI Solutions: This domain covers the security measures, compliance requirements, and governance practices essential for managing AI solutions. It targets security professionals, compliance officers, and IT managers responsible for safeguarding AI systems, ensuring regulatory compliance, and implementing effective governance frameworks.
Topic 3
- Fundamentals of Generative AI: This domain explores the basics of generative AI, focusing on techniques for creating new content from learned patterns, including text and image generation. It targets professionals interested in understanding generative models, such as developers and researchers in AI.
Topic 4
- Guidelines for Responsible AI: This domain highlights the ethical considerations and best practices for deploying AI solutions responsibly, including ensuring fairness and transparency. It is aimed at AI practitioners, including data scientists and compliance officers, who are involved in the development and deployment of AI systems and need to adhere to ethical standards.
Topic 5
- Fundamentals of AI and ML: This domain covers the fundamental concepts of artificial intelligence (AI) and machine learning (ML), including core algorithms and principles. It is aimed at individuals new to AI and ML, such as entry-level data scientists and IT professionals.
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Amazon AWS Certified AI Practitioner Sample Questions (Q131-Q136):
NEW QUESTION # 131
An animation company wants to provide subtitles for its content. Which AWS service meets this requirement?
- A. Amazon Transcribe
- B. Amazon Translate
- C. Amazon Polly
- D. Amazon Comprehend
Answer: A
Explanation:
Amazon Transcribe is the AWS service that converts speech to text, enabling the generation of subtitles (closed captions) for audio and video content automatically.
C is correct:
"Amazon Transcribe is an automatic speech recognition (ASR) service that makes it easy for developers to add speech-to-text capability to applications." This feature supports creating subtitles and transcripts for media files.
(Reference: Amazon Transcribe Overview, AWS AI Practitioner Official Study Guide) This feature supports creating subtitles and transcripts for media files.
"Amazon Transcribe is an automatic speech recognition (ASR) service that makes it easy for developers to add speech-to-text capability to applications." This feature supports creating subtitles and transcripts for media files.
(Reference: Amazon Transcribe Overview, AWS AI Practitioner Official Study Guide) A (Comprehend) is for NLP/text analytics.
B (Polly) is text-to-speech.
D (Translate) translates text, but does not create subtitles from audio/video.
NEW QUESTION # 132
A law firm wants to build an AI application by using large language models (LLMs). The application will read legal documents and extract key points from the documents.
Which solution meets these requirements?
- A. Develop a summarization chatbot.
- B. Develop a multi-language translation system.
- C. Build an automatic named entity recognition system.
- D. Create a recommendation engine.
Answer: A
NEW QUESTION # 133
A company is using the Generative AI Security Scoping Matrix to assess security responsibilities for its solutions. The company has identified four different solution scopes based on the matrix.
Which solution scope gives the company the MOST ownership of security responsibilities?
- A. Building an application by using an existing third-party generative AI foundation model (FM).
- B. Using a third-party enterprise application that has embedded generative AI features.
- C. Building and training a generative AI model from scratch by using specific data that a customer owns.
- D. Refining an existing third-party generative AI foundation model (FM) by fine-tuning the model by using data specific to the business.
Answer: C
Explanation:
Building and training a generative AI model from scratch provides the company with the most ownership and control over security responsibilities. In this scenario, the company is responsible for all aspects of the security of the data, the model, and the infrastructure.
* Option D (Correct): "Building and training a generative AI model from scratch by using specific data that a customer owns": This is the correct answer because it involves complete ownership of the model, data, and infrastructure, giving the company the highest level of responsibility for security.
* Option A: "Using a third-party enterprise application that has embedded generative AI features" is incorrect as the company has minimal control over the security of the AI features embedded within a third-party application.
* Option B: "Building an application using an existing third-party generative AI foundation model (FM)" is incorrect because security responsibilities are shared with the third-party model provider.
* Option C: "Refining an existing third-party generative AI FM by fine-tuning the model with business- specific data" is incorrect as the foundation model and part of the security responsibilities are still managed by the third party.
AWS AI Practitioner References:
* Generative AI Security Scoping Matrix on AWS: AWS provides a security responsibility matrix that outlines varying levels of control and responsibility depending on the approach to developing and using AI models.
NEW QUESTION # 134
A company wants to develop a large language model (LLM) application by using Amazon Bedrock and customer data that is uploaded to Amazon S3. The company's security policy states that each team can access data for only the team's own customers.
Which solution will meet these requirements?
- A. Create one Amazon Bedrock role that has full Amazon S3 access. Create IAM roles for each team that have access to only each team's customer folders.
- B. Create a custom service role that has Amazon S3 access. Ask teams to specify the customer name on each Amazon Bedrock request.
- C. Create an Amazon Bedrock custom service role for each team that has access to only the team's customer data.
- D. Redact personal data in Amazon S3. Update the S3 bucket policy to allow team access to customer data.
Answer: C
NEW QUESTION # 135
In which stage of the generative AI model lifecycle are tests performed to examine the model's accuracy?
- A. Data selection
- B. Deployment
- C. Evaluation
- D. Fine-tuning
Answer: C
Explanation:
The evaluation stage of the generative AI model lifecycle involves testing the model to assess its performance, including accuracy, coherence, and other metrics. This stage ensures the model meets the desired quality standards before deployment.
Exact Extract from AWS AI Documents:
From the AWS AI Practitioner Learning Path:
"The evaluation phase in the machine learning lifecycle involves testing the model against validation or test datasets to measure its performance metrics, such as accuracy, precision, recall, or task-specific metrics for generative AI models." (Source: AWS AI Practitioner Learning Path, Module on Machine Learning Lifecycle) Detailed Option A: DeploymentDeployment involves making the model available for use in production. While monitoring occurs post-deployment, accuracy testing is performed earlier in the evaluation stage.
Option B: Data selectionData selection involves choosing and preparing data for training, not testing the model's accuracy.
Option C: Fine-tuningFine-tuning adjusts a pre-trained model to improve performance for a specific task, but it is not the stage where accuracy is formally tested.
Option D: EvaluationThis is the correct answer. The evaluation stage is where tests are conducted to examine the model's accuracy and other performance metrics, ensuring it meets requirements.
Reference:
AWS AI Practitioner Learning Path: Module on Machine Learning Lifecycle Amazon SageMaker Developer Guide: Model Evaluation (https://docs.aws.amazon.com/sagemaker/latest/dg/model-evaluation.html) AWS Documentation: Generative AI Lifecycle (https://aws.amazon.com/machine-learning/)
NEW QUESTION # 136
......
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AIF-C01 Valid Practice Materials - Exam AIF-C01 Questions Fee
BONUS!!! Download part of PDFTorrent AIF-C01 dumps for free: https://drive.google.com/open?id=1kWZPCYvIsGiWGNrC-pPEnILAtHzDdr1W
AIF-C01 practice test keeps a record of your attempts so you can evaluate and enhance your progress. Our AWS Certified AI Practitioner (AIF-C01) practice exams replicate the real AWS Certified AI Practitioner (AIF-C01) exam environment so you can eliminate your anxiety. You can access the web-based AWS Certified AI Practitioner (AIF-C01) practice exam through browsers. Moreover, operating systems such as Mac, iOS, Android, Windows, and Linux support the online AIF-C01 practice exam.
Amazon AIF-C01 Exam Syllabus Topics:
Topic
Details
Topic 1
Topic 2
Topic 3
Topic 4
Topic 5
>> AIF-C01 Valid Practice Materials <<
Pass Guaranteed Quiz 2025 Amazon AIF-C01: AWS Certified AI Practitioner – High-quality Valid Practice Materials
All these three AWS Certified AI Practitioner (AIF-C01) exam questions formats contain the actual, updated, and error-free AWS Certified AI Practitioner (AIF-C01) exam practice test questions that assist you in AWS Certified AI Practitioner (AIF-C01) exam preparation. Finally, With the Amazon AIF-C01 Exam Questions you will be ready to get success in the final Amazon AIF-C01 certification exam. Please choose the best AWS Certified AI Practitioner (AIF-C01) exam questions format and download it quickly and start this journey today.
Amazon AWS Certified AI Practitioner Sample Questions (Q131-Q136):
NEW QUESTION # 131
An animation company wants to provide subtitles for its content. Which AWS service meets this requirement?
Answer: A
Explanation:
Amazon Transcribe is the AWS service that converts speech to text, enabling the generation of subtitles (closed captions) for audio and video content automatically.
C is correct:
"Amazon Transcribe is an automatic speech recognition (ASR) service that makes it easy for developers to add speech-to-text capability to applications." This feature supports creating subtitles and transcripts for media files.
(Reference: Amazon Transcribe Overview, AWS AI Practitioner Official Study Guide) This feature supports creating subtitles and transcripts for media files.
"Amazon Transcribe is an automatic speech recognition (ASR) service that makes it easy for developers to add speech-to-text capability to applications." This feature supports creating subtitles and transcripts for media files.
(Reference: Amazon Transcribe Overview, AWS AI Practitioner Official Study Guide) A (Comprehend) is for NLP/text analytics.
B (Polly) is text-to-speech.
D (Translate) translates text, but does not create subtitles from audio/video.
NEW QUESTION # 132
A law firm wants to build an AI application by using large language models (LLMs). The application will read legal documents and extract key points from the documents.
Which solution meets these requirements?
Answer: A
NEW QUESTION # 133
A company is using the Generative AI Security Scoping Matrix to assess security responsibilities for its solutions. The company has identified four different solution scopes based on the matrix.
Which solution scope gives the company the MOST ownership of security responsibilities?
Answer: C
Explanation:
Building and training a generative AI model from scratch provides the company with the most ownership and control over security responsibilities. In this scenario, the company is responsible for all aspects of the security of the data, the model, and the infrastructure.
* Option D (Correct): "Building and training a generative AI model from scratch by using specific data that a customer owns": This is the correct answer because it involves complete ownership of the model, data, and infrastructure, giving the company the highest level of responsibility for security.
* Option A: "Using a third-party enterprise application that has embedded generative AI features" is incorrect as the company has minimal control over the security of the AI features embedded within a third-party application.
* Option B: "Building an application using an existing third-party generative AI foundation model (FM)" is incorrect because security responsibilities are shared with the third-party model provider.
* Option C: "Refining an existing third-party generative AI FM by fine-tuning the model with business- specific data" is incorrect as the foundation model and part of the security responsibilities are still managed by the third party.
AWS AI Practitioner References:
* Generative AI Security Scoping Matrix on AWS: AWS provides a security responsibility matrix that outlines varying levels of control and responsibility depending on the approach to developing and using AI models.
NEW QUESTION # 134
A company wants to develop a large language model (LLM) application by using Amazon Bedrock and customer data that is uploaded to Amazon S3. The company's security policy states that each team can access data for only the team's own customers.
Which solution will meet these requirements?
Answer: C
NEW QUESTION # 135
In which stage of the generative AI model lifecycle are tests performed to examine the model's accuracy?
Answer: C
Explanation:
The evaluation stage of the generative AI model lifecycle involves testing the model to assess its performance, including accuracy, coherence, and other metrics. This stage ensures the model meets the desired quality standards before deployment.
Exact Extract from AWS AI Documents:
From the AWS AI Practitioner Learning Path:
"The evaluation phase in the machine learning lifecycle involves testing the model against validation or test datasets to measure its performance metrics, such as accuracy, precision, recall, or task-specific metrics for generative AI models." (Source: AWS AI Practitioner Learning Path, Module on Machine Learning Lifecycle) Detailed Option A: DeploymentDeployment involves making the model available for use in production. While monitoring occurs post-deployment, accuracy testing is performed earlier in the evaluation stage.
Option B: Data selectionData selection involves choosing and preparing data for training, not testing the model's accuracy.
Option C: Fine-tuningFine-tuning adjusts a pre-trained model to improve performance for a specific task, but it is not the stage where accuracy is formally tested.
Option D: EvaluationThis is the correct answer. The evaluation stage is where tests are conducted to examine the model's accuracy and other performance metrics, ensuring it meets requirements.
Reference:
AWS AI Practitioner Learning Path: Module on Machine Learning Lifecycle Amazon SageMaker Developer Guide: Model Evaluation (https://docs.aws.amazon.com/sagemaker/latest/dg/model-evaluation.html) AWS Documentation: Generative AI Lifecycle (https://aws.amazon.com/machine-learning/)
NEW QUESTION # 136
......
Your dream is very high, so you have to find a lot of material to help you prepare for the exam. PDFTorrent Amazon AIF-C01 Exam Materials can help you to achieve your ideal. PDFTorrent Amazon AIF-C01 exam materials is a collection of experience and innovation from highly certified IT professionals in the field. Our products will let you try all the problems that may arise in a really examinations. We can give you a guarantee, to ensure that candidates get a 100% correct answer.
Exam AIF-C01 Questions Fee: https://www.pdftorrent.com/AIF-C01-exam-prep-dumps.html
BTW, DOWNLOAD part of PDFTorrent AIF-C01 dumps from Cloud Storage: https://drive.google.com/open?id=1kWZPCYvIsGiWGNrC-pPEnILAtHzDdr1W