Amazon AWS Certified AI Practitioner AIF-C01 Dumps in PDF

Free Amazon AIF-C01 Real Questions (page: 4)

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?

  1. Create an Amazon Bedrock custom service role for each team that has access to only the team's customer data.
  2. Create a custom service role that has Amazon S3 access. Ask teams to specify the customer name on each
    Amazon Bedrock request.
  3. Redact personal data in Amazon S3. Update the S3 bucket policy to allow team access to customer data.
  4. 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.

Answer(s): A

Explanation:

Creating a custom Amazon Bedrock service role for each team with restricted access to only the team's customer data ensures compliance with the security policy, providing the necessary data segregation and access control. The other options do not effectively enforce team-specific access or may pose risks of broader access than allowed by the policy.



A retail company wants to add a virtual shopping assistant to its website. The assistant must answer product questions in natural language and continue the interaction when customers ask follow-up questions in different ways.
Which capability of generative AI (GenAI) supports these requirements?

  1. Generates context-aware replies during multi-turn conversations
  2. Guarantees identical replies for repeated customer questions
  3. Answers accurately without access to company product data
  4. Completely removes the need for human review of customer-facing outputs

Answer(s): A

Explanation:

Generative AI can maintain conversational context across multiple turns, allowing a virtual shopping assistant to understand follow-up questions even when customers phrase them differently. This supports natural,
context-aware interactions about products over the course of a conversation.



A company built an AI-powered resume screening system. The company used a large dataset to train the model. The dataset contained resumes that were not representative of all demographics.
Which core dimension of responsible AI does this scenario present?

  1. Fairness
  2. Explainability
  3. Privacy and security
  4. Transparency

Answer(s): A

Explanation:

The scenario describes a dataset that is not representative of all demographics, which can lead to biased model predictions. This directly relates to fairness, a core dimension of responsible AI that ensures AI systems make unbiased and equitable decisions across different demographic groups. Addressing fairness involves techniques such as balanced dataset curation, bias detection, and mitigation strategies to ensure that the AI
system does not discriminate against any group.



A company wants to set up private access to Amazon Bedrock APIs from the company’s AWS account. The company also wants to protect its data from internet exposure.
Which solution meets these requirements?

  1. Use Amazon CloudFront to restrict access to the company’s private content.
  2. Use AWS Glue to set up data encryption across the company’s data catalog.
  3. Use AWS Lake Formation to manage centralized data governance and cross-account data sharing.
  4. Use AWS PrivateLink to configure a private connection between the company’s VPC and Amazon Bedrock.

Answer(s): D

Explanation:

AWS PrivateLink enables private connectivity between your VPC and Amazon Bedrock APIs without exposing data to the public internet, ensuring that all API calls and data transfers remain secure and private within your
AWS account.



A company plans to build an AI model for the company’s global customer base. The company wants to train the model on a dataset that reflects user diversity.
Which action will meet this requirement?

  1. Balance class representation in the dataset.
  2. Use a regional dataset with complete data.
  3. Oversample majority class data.
  4. Drop minority class data records.

Answer(s): A

Explanation:

Balancing class representation ensures that all groups in the dataset are adequately represented, which helps the model learn patterns across diverse users and reduces bias.



A company is working on a large language model (LLM) and noticed that the LLM’s outputs are not as diverse as expected.
Which parameter should the company adjust?

  1. Temperature
  2. Batch size
  3. Learning rate
  4. Optimizer type

Answer(s): A

Explanation:

The “temperature” parameter controls the randomness and diversity of outputs generated by a large language model. Increasing the temperature produces more diverse and creative responses, while lowering it makes the outputs more focused and deterministic.



A large retail bank wants to develop an ML system to help the risk management team decide on loan allocations for different demographics.
What must the bank do to develop an unbiased ML model?

  1. Reduce the size of the training dataset.
  2. Ensure that the ML model predictions are consistent with historical results.
  3. Create a different ML model for each demographic group.
  4. Measure class imbalance on the training dataset. Adapt the training process accordingly.

Answer(s): D

Explanation:

In machine learning, class imbalance occurs when certain classes are underrepresented in the training dataset,
leading to biased model predictions. To develop an unbiased model, it's crucial to assess the class distribution and adjust the training process to address any imbalances. This can be achieved through techniques such as oversampling the minority class, undersampling the majority class, or applying class weights to ensure the model treats all classes equitably.



A company needs to log all requests made to its Amazon Bedrock API. The company must retain the logs securely for 5 years at the lowest possible cost.
Which combination of AWS service and storage class meets these requirements? (Choose two.)

  1. AWS CloudTrail
  2. Amazon CloudWatch
  3. AWS Audit Manager
  4. Amazon S3 Intelligent-Tiering
  5. Amazon S3 Standard

Answer(s): A,D

Explanation:

AWS CloudTrail is the AWS service designed for logging and monitoring API calls made to AWS services,
including Amazon Bedrock. CloudTrail records detailed information about the API requests, including the identity of the requester, the time of the request, and the source IP address. This service is ideal for logging all requests made to the Amazon Bedrock API and meets the logging requirement.
Amazon S3 Intelligent-Tiering is a storage class designed for storing data that has unpredictable access patterns. It automatically moves data between two access tiers (frequent and infrequent) based on usage,
which helps reduce costs while ensuring data is still available when needed. For retaining logs securely over 5
years at the lowest possible cost, this storage class provides an efficient way to handle long-term storage requirements without incurring unnecessary costs.



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