100% Pass Quiz 2025 Amazon Updated AIF-C01: AWS Certified AI Practitioner Answers Free

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We strongly recommend using our AWS Certified AI Practitioner (AIF-C01) exam dumps to prepare for the Amazon AIF-C01 certification. It is the best way to ensure success. With our AWS Certified AI Practitioner (AIF-C01) practice questions, you can get the most out of your studying and maximize your chances of passing your AWS Certified AI Practitioner (AIF-C01) exam.

Amazon AIF-C01 Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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 3	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.
Topic 4	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 5	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.

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Amazon AWS Certified AI Practitioner Sample Questions (Q165-Q170):

NEW QUESTION # 165
A company has built an image classification model to predict plant diseases from photos of plant leaves. The company wants to evaluate how many images the model classified correctly.
Which evaluation metric should the company use to measure the model's performance?

A. Accuracy
B. Learning rate
C. R-squared score
D. Root mean squared error (RMSE)

Answer: A

NEW QUESTION # 166
A company wants to build an ML application.
Select and order the correct steps from the following list to develop a well-architected ML workload. Each step should be selected one time. (Select and order FOUR.)
* Deploy model
* Develop model
* Monitor model
* Define business goal and frame ML problem

Answer:

Explanation:

Reference:
AWS AI Practitioner Learning Path: Module on Machine Learning Lifecycle Amazon SageMaker Developer Guide: Machine Learning Workflow (https://docs.aws.amazon.com/sagemaker/latest/dg/how-it-works-mlconcepts.html) AWS Well-Architected Framework: Machine Learning Lens (https://docs.aws.amazon.com/wellarchitected/latest/machine-learning-lens/)

NEW QUESTION # 167
A company wants to collaborate with several research institutes to develop an AI model. The company needs standardized documentation of model version tracking and a record of model development.
Which solution meets these requirements?

A. Track the model changes by using Amazon SageMaker Model Cards.
B. Track the model changes by using Git.
C. Track the model changes by using Amazon Fraud Detector.
D. Track the model changes by using Amazon Comprehend.

Answer: A

Explanation:
Amazon SageMaker Model Cards provide a standardized way to document and track model information, including versions and performance. According to AWS documentation:
Explanation:
Amazon SageMaker Model Cards provide a standardized way to document and track model information, including versions and performance. According to AWS documentation:
"SageMaker Model Cards provide a single source of truth for model information including intended use, training details, evaluation metrics, and ethical considerations to support governance and collaboration."

NEW QUESTION # 168
A customer service team is developing an application to analyze customer feedback and automatically classify the feedback into different categories. The categories include product quality, customer service, and delivery experience.
Which AI concept does this scenario present?

A. Computer vision
B. Fraud detection
C. Recommendation systems
D. Natural language processing (NLP)

Answer: D

Explanation:
The scenario involves analyzing customer feedback and automatically classifying it into categories such as product quality, customer service, and delivery experience. This task requires processing and understanding textual data, which is a core application of natural language processing (NLP). NLP encompasses techniques for analyzing, interpreting, and generating human language, including tasks like text classification, sentiment analysis, and topic modeling, all of which are relevant to this use case.
Exact Extract from AWS AI Documents:
From the AWS AI Practitioner Learning Path:
"Natural Language Processing (NLP) enables machines to understand and process human language.
Common NLP tasks include text classification, sentiment analysis, named entity recognition, and topic modeling. Services like Amazon Comprehend can be used to classify text into predefined categories based on content." (Source: AWS AI Practitioner Learning Path, Module on AI and ML Concepts) Detailed Explanation:
* Option A: Computer visionComputer vision involves processing and analyzing visual data, such as images or videos. Since the scenario deals with textual customer feedback, computer vision is not applicable.
* Option B: Natural language processing (NLP)This is the correct answer. The task of classifying customer feedback into categories requires understanding and processing text, which is an NLP task.
AWS services like Amazon Comprehend are specifically designed for such text classification tasks.
* Option C: Recommendation systemsRecommendation systems suggest items or content based on user preferences or behavior. The scenario does not involve recommending products or services but rather classifying feedback, so this option is incorrect.
* Option D: Fraud detectionFraud detection involves identifying anomalous or fraudulent activities, typically in financial or transactional data. The scenario focuses on text classification, not anomaly detection, making this option irrelevant.
References:
AWS AI Practitioner Learning Path: Module on AI and ML Concepts
Amazon Comprehend Developer Guide: Text Classification (https://docs.aws.amazon.com/comprehend/latest
/dg/how-classification.html)
AWS Documentation: Introduction to NLP (https://aws.amazon.com/what-is/natural-language-processing/)

NEW QUESTION # 169
An ML research team develops custom ML models. The model artifacts are shared with other teams for integration into products and services. The ML team retains the model training code and data. The ML team wants to builk a mechanism that the ML team can use to audit models.
Which solution should the ML team use when publishing the custom ML models?

A. Use AWS A] Service Cards for transparency and understanding models.
B. Create Amazon SageMaker Model Cards with Intended uses and training and inference details.
C. Create documents with the relevant information. Store the documents in Amazon S3.
D. Create model training scripts. Commit the model training scripts to a Git repository.

Answer: B

Explanation:
The ML research team needs a mechanism to audit custom ML models while sharing model artifacts with other teams. Amazon SageMaker Model Cards provide a structured way todocument model details, including intended uses, training data, and inference performance, making them ideal for auditing and ensuring transparency when publishing models.
Exact Extract from AWS AI Documents:
From the Amazon SageMaker Developer Guide:
"Amazon SageMaker Model Cards enable you to document critical details about your machine learning models, such as intended uses, training data, evaluation metrics, and inference details. Model Cards support auditing by providing a centralized record that can be reviewed by teams to understand model behavior and limitations." (Source: Amazon SageMaker Developer Guide, SageMaker Model Cards) Detailed Explanation:
Option A: Create documents with the relevant information. Store the documents in Amazon S3.While storing documents in S3 is feasible, it lacks the structured format and integration with SageMaker that Model Cards provide, making it less suitable for auditing purposes.
Option B: Use AWS AI Service Cards for transparency and understanding models.AWS AI Service Cards are not a standard feature in AWS documentation. This option appears to be a distractor and is not a valid solution.
Option C: Create Amazon SageMaker Model Cards with Intended uses and training and inference details.This is the correct answer. SageMaker Model Cards are specifically designed to document model details for auditing, transparency, and collaboration, meeting the team's requirements.
Option D: Create model training scripts. Commit the model training scripts to a Git repository.Sharing training scripts in a Git repository provides access to code but does not offer a structured auditing mechanism for model details like intended uses or inference performance.
References:
Amazon SageMaker Developer Guide: SageMaker Model Cards (https://docs.aws.amazon.com/sagemaker
/latest/dg/model-cards.html)
AWS AI Practitioner Learning Path: Module on Model Governance and Auditing AWS Documentation: Responsible AI with SageMaker (https://aws.amazon.com/sagemaker/)

NEW QUESTION # 170
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100% PASS QUIZ 2025 AMAZON UPDATED AIF-C01: AWS CERTIFIED AI PRACTITIONER ANSWERS FREE

100% Pass Quiz 2025 Amazon Updated AIF-C01: AWS Certified AI Practitioner Answers Free