Free AIF-C01 Exam Braindumps
AWS Certified AI Practitioner (page: 14)

Updated On: 19-Oct-2026

A company is introducing a new feature for its application. The feature will refine the style of output messages.
The company will fine-tune a large language model (LLM) on Amazon Bedrock to implement the feature.
Which type of data does the company need to meet these requirements?

  1. Samples of only input messages
  2. Samples of only output messages
  3. Samples of pairs of input and output messages
  4. Separate samples of input and output messages

Answer(s): C

Explanation:

Fine-tuning a large language model to refine the style of output messages requires training data consisting of paired input and output messages. These pairs allow the model to learn the relationship between the input provided and the desired styled output, ensuring the fine-tuned model produces responses with the intended style.



A social media company wants to prevent users from posting discriminatory content on the company's application. The company wants to use Amazon Bedrock as part of the solution.
How can the company use Amazon Bedrock to meet these requirements?

  1. Give users the ability to interact based on user preferences.
  2. Block interactions related to predefined topics.
  3. Restrict user conversations to predefined topics.
  4. Provide a variety of responses to select from for user engagement.

Answer(s): B

Explanation:

Amazon Bedrock’s built-in content moderation lets you define categories or keywords (e.g., hate speech,
discriminatory language) and automatically block or filter any user inputs or outputs that fall under those topics.
By configuring Bedrock’s safety filters with your predefined “disallowed” categories, the application will prevent discriminatory content from ever being posted.



A global logistics company is using generative AI (GenAI) models on Amazon Bedrock to automate paperwork and shipment documentation. The company wants to set up a clear AI governance process to make sure the models are used responsibly and meet company policies.
Which solutions will meet these requirements? (Choose two.)

  1. Set up a regular review process to check that the models' results are accurate and fair and follow company policies.
  2. Provide training for all employees who work with AI tools so the employees understand company rules, data handling, and responsible AI use.
  3. Let the cloud provider manage all AI safety checks and reviews to save internal effort.
  4. Involve only developers in governance reviews because the developers build and deploy the AI systems.
  5. Review the models only when users report problems or errors in the system.

Answer(s): A,B

Explanation:

A regular review process helps verify that generative AI outputs remain accurate, fair, and aligned with company policies. Employee training ensures that people who use AI tools understand responsible AI
practices, data handling expectations, and governance requirements.



A company wants to assess internet quality in remote areas of the world. The company needs to collect internet speed data and store the data in Amazon RDS. The company will analyze internet speed variation throughout each day. The company wants to create an AI model to predict potential internet disruptions.
Which type of data should the company collect for this task?

  1. Tabular data
  2. Text data
  3. Time series data
  4. Audio data

Answer(s): C

Explanation:

Time series data consists of measurements (such as internet speed) collected over time, which is essential for analyzing variations throughout the day and for building predictive models of potential internet disruptions.



A company is deploying AI/ML models by using AWS services. The company wants to offer transparency into the models’ decision-making processes and provide explanations for the model outputs.
Which AWS service or feature meets these requirements?

  1. Amazon SageMaker Model Cards
  2. Amazon Rekognition
  3. Amazon Comprehend
  4. Amazon Lex

Answer(s): A

Explanation:

Amazon SageMaker Model Cards help provide transparency into AI/ML models by documenting key details such as model purpose, training data, performance metrics, and limitations. This documentation enables organizations to explain model outputs and decision-making processes, ensuring accountability and compliance with responsible AI principles.



Viewing page 14 of 108
Viewing questions 66 - 70 out of 535 questions


Post your Comments and Discuss Amazon AIF-C01 exam prep with other Community members:

AI Tutor AI Tutor 👋 I’m here to help!