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Amazon AIF-C01 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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
  • 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 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 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 (Q199-Q204):

NEW QUESTION # 199
A financial company has offices in different countries worldwide. The company requires that all API calls between generative AI applications and foundation models (FM) must not travel across the public internet.
Which AWS service should the company use?

Answer: C

Explanation:
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.


NEW QUESTION # 200
A company wants to develop ML applications to improve business operations and efficiency.
Select the correct ML paradigm from the following list for each use case. Each ML paradigm should be selected one or more times. (Select FOUR.)
* Supervised learning
* Unsupervised learning

Answer:

Explanation:

.
Reference:
AWS AI Practitioner Learning Path: Module on Machine Learning Strategies Amazon SageMaker Developer Guide: Supervised and Unsupervised Learning (https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html) AWS Documentation: Introduction to Machine Learning Paradigms (https://aws.amazon.com/machine-learning/)


NEW QUESTION # 201
A company is monitoring a predictive model by using Amazon SageMaker Model Monitor. The company notices data drift beyond a defined threshold. The company wants to mitigate a potentially adverse impact on the predictive model.

Answer: A

Explanation:
The correct answer is C - Re-train the model with fresh data. AWS SageMaker Model Monitor is designed to detect data drift, feature drift, and model quality degradation in real-time. When drift exceeds a set threshold, AWS recommends initiating a retraining workflow with updated data to restore model accuracy. According to AWS documentation, data drift indicates that the distribution of incoming data has changed significantly from the original training dataset-often due to new user behaviors, market changes, or seasonal patterns.
Restarting the endpoint (A) does not address degraded model performance. Adjusting sensitivity (B) suppresses the alert but does not fix the underlying issue. Experiments tracking (D) is helpful for monitoring model versions but is not corrective. Retraining ensures the model adapts to new data patterns and continues to perform reliably, which is the AWS-endorsed response to drift detection alerts.
Referenced AWS Documentation:
* Amazon SageMaker Model Monitor - Detecting Drift
* AWS ML Ops Best Practices - Continuous Retraining


NEW QUESTION # 202
A company is implementing the Amazon Titan foundation model (FM) by using Amazon Bedrock. The company needs to supplement the model by using relevant data from the company's private data sources.
Which solution will meet this requirement?

Answer: D

Explanation:
Creating an Amazon Bedrock knowledge base allows the integration of external or private data sources with a foundation model (FM) like Amazon Titan. This integration helps supplement the model with relevant data from the company's private data sources to enhance its responses.
Option C (Correct): "Create an Amazon Bedrock knowledge base": This is the correct answer as it enables the company to incorporate private data into the FM to improve its effectiveness.
Option A: "Use a different FM" is incorrect because it does not address the need to supplement the current model with private data.
Option B: "Choose a lower temperature value" is incorrect as it affects output randomness, not the integration of private data.
Option D: "Enable model invocation logging" is incorrect because logging does not help in supplementing the model with additional data.
AWS AI Practitioner Reference:
Amazon Bedrock and Knowledge Integration: AWS explains how creating a knowledge base allows Amazon Bedrock to use external data sources to improve the FM's relevance and accuracy.


NEW QUESTION # 203
A company wants to create a new solution by using AWS Glue. The company has minimal programming experience with AWS Glue.
Which AWS service can help the company use AWS Glue?

Answer: C

Explanation:
AWS Glue is a serverless data integration service that enables users to extract, transform, and load (ETL) data. For a company with minimal programming experience, Amazon Q Developer provides an AI-powered assistant that can generate code, explain AWS services, and guide users through tasks like creating AWS Glue jobs. This makes it an ideal tool to help the company use AWS Glue effectively.
Exact Extract from AWS AI Documents:
From the AWS Documentation on Amazon Q Developer:
"Amazon Q Developer is an AI-powered assistant that helps developers by generating code, answering questions about AWS services, and providing step-by-step guidance for tasks such as building ETL pipelines with AWS Glue. It is designed to assist users with varying levels of expertise, including those with minimal programming experience." (Source: AWS Documentation, Amazon Q Developer Overview) Detailed Option A: Amazon Q Developer This is the correct answer. Amazon Q Developer can assist the company by generating AWS Glue scripts, explaining Glue concepts, and providing guidance on setting up ETL jobs, which is particularly helpful for users with limited programming experience.
Option B: AWS Config
AWS Config is used for tracking and managing resource configurations and compliance, not for assisting with coding or using services like AWS Glue. This option is incorrect.
Option C: Amazon Personalize
Amazon Personalize is a machine learning service for building recommendation systems, not for assisting with data integration or AWS Glue. This option is irrelevant.
Option D: Amazon Comprehend
Amazon Comprehend is an NLP service for analyzing text, not for helping users write code or use AWS Glue. This option does not meet the requirements.
Reference:
AWS Documentation: Amazon Q Developer Overview (https://aws.amazon.com/q/developer/) AWS Glue Developer Guide: Introduction to AWS Glue (https://docs.aws.amazon.com/glue/latest/dg/what-is-glue.html) AWS AI Practitioner Learning Path: Module on AWS Developer Tools and Services


NEW QUESTION # 204
......

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