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The Amazon sector is an ever-evolving and rapidly growing industry that is crucial in shaping our lives today. With the growing demand for skilled Amazon professionals, obtaining AWS Certified AI Practitioner (AIF-C01) certification exam has become increasingly important for those who are looking to advance their careers and stay competitive in the job market. Individuals who hold AWS Certified AI Practitioner (AIF-C01) certification exam demonstrate to their employers and clients that they have the knowledge and skills necessary to succeed in the AIF-C01 exam.

Amazon AWS Certified AI Practitioner Sample Questions (Q349-Q354):

NEW QUESTION # 349
A company is training its employees on how to structure prompts for foundation models.
Select the correct prompt engineering technique from the following list for each prompt template. Each prompt engineering technique should be selected onetime. (SelectTHREE.)
* Chain-of-thought reasoning
* Few-shot learning
* Zero-shot learning

Answer:

Explanation:


NEW QUESTION # 350
A company is using an Amazon Bedrock base model to summarize documents for an internal use case. The company trained a custom model to improve the summarization quality.
Which action must the company take to use the custom model through Amazon Bedrock?

Answer: B


NEW QUESTION # 351
An ecommerce company is developing an AI application that categorizes product images and extracts specifications. The application will use a high-quality labeled dataset to customize a foundation model (FM) to generate accurate responses.
Which ML technique will meet these requirements by using Amazon Bedrock?

Answer: D

Explanation:
Comprehensive and Detailed Explanation From Exact AWS AI documents:
The correct technique is fine-tuning, which is explicitly supported by Amazon Bedrock for customizing foundation models using high-quality labeled datasets.
Fine-tuning involves:
* Starting with a pre-trained foundation model
* Training it further using domain-specific, labeled data
* Improving accuracy for specialized tasks, such as product classification, image-based understanding, and specification extraction In this use case:
* The company has labeled data
* They want to customize model behavior
* They require high accuracy and domain adaptation
These conditions match the definition of fine-tuning, not prompt-only methods.
Why the other options are incorrect:
* A. Continued pre-training typically requires massive unlabeled datasets and is not the standard customization method exposed in Amazon Bedrock.
* B. Creating an agent orchestrates model interactions and tools but does not customize the model's learned parameters.
* D. Prompt engineering improves responses through prompt design but does not modify the underlying model weights, making it insufficient for deep domain adaptation.
AWS AI document references (for exact extracts):
* Amazon Bedrock Documentation - section on Model customization and fine-tuning
* AWS Generative AI Study Guide - comparison of prompt engineering vs fine-tuning
* Foundation Models on AWS - explanation of fine-tuning with labeled datasets


NEW QUESTION # 352
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.
Which AWS service can the company use to meet this requirement?

Answer: B

Explanation:
AWS Data Exchange is a service that allows companies to securely exchange data with third parties, such as independent software vendors (ISVs). AWS Data Exchange can be configured to provide notifications, including email notifications, when new datasets or compliance reports become available.
* Option D (Correct): "AWS Data Exchange": This is the correct answer because it enables the company to receive notifications, including email messages, when ISVs' compliance reports are available.
* Option A: "AWS Audit Manager" is incorrect because it focuses on assessing an organization's own compliance, not receiving third-party compliance reports.
* Option B: "AWS Artifact" is incorrect as it provides access to AWS's compliance reports, not ISVs'.
* Option C: "AWS Trusted Advisor" is incorrect as it offers optimization and best practices guidance, not compliance report notifications.
AWS AI Practitioner References:
* AWS Data Exchange Documentation: AWS explains how Data Exchange allows organizations to subscribe to third-party data and receive notifications when updates are available.


NEW QUESTION # 353
A company wants to deploy a conversational chatbot to answer customer questions. The chatbot is based on a fine-tuned Amazon SageMaker JumpStart model. The application must comply with multiple regulatory frameworks.
Which capabilities can the company show compliance for? (Select TWO.)

Answer: D,E

Explanation:
Let me know if you'd like to continue with any more questions or if you need further assistance!


NEW QUESTION # 354
......

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