This is the free Amazon AIF-C01 practice question bank —
230 of 443 total questions, each with a full explanation, free to
read with no signup required. Updated 2026-08-05.
Every answer is verified against official Amazon documentation —
see our methodology.
Question 1
Which AWS service provides a broad range of high-performing generative AI foundation models (FMs)?
A. Amazon Bedrock
B. Amazon Rekognition
C. Amazon Lex
D. Amazon Kendra
Show Answer
Correct Answer: A
Explanation: Amazon Bedrock is the AWS service that provides access to a broad range of high-performing generative AI foundation models (FMs) from Amazon and third-party providers through a fully managed service. Amazon Rekognition is for image/video analysis, Amazon Lex is for conversational chatbots, and Amazon Kendra is an intelligent enterprise search service.
Question 2
A company is using Retrieval Augmented Generation (RAG) in its generative AI (GenAI) application. The company wants to use Amazon Bedrock Knowledge Bases evaluations to measure how well responses avoid hallucination based on the retrieved texts.
Which metric meets these requirements?
A. Refusal
B. Harmfulness
C. Stereotyping
D. Faithfulness
Show Answer
Correct Answer: D
Explanation: Faithfulness measures whether the generated response is supported by and consistent with the retrieved context, making it the key metric for detecting and minimizing hallucinations in Retrieval Augmented Generation (RAG). Refusal measures appropriate refusal behavior, Harmfulness evaluates unsafe content, and Stereotyping evaluates bias rather than grounding.
Question 3
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.)
A. Set up a regular review process to check that the models' results are accurate and fair and follow company policies.
B. Provide training for all employees who work with AI tools so the employees understand company rules, data handling, and responsible AI use.
C. Let the cloud provider manage all AI safety checks and reviews to save internal effort.
D. Involve only developers in governance reviews because the developers build and deploy the AI systems.
E. Review the models only when users report problems or errors in the system.
Show Answer
Correct Answer: A, B
Explanation: Effective AI governance includes ongoing oversight of model behavior and organizational processes. Regular reviews help ensure outputs remain accurate, fair, and aligned with company policies. Employee training is a core governance practice so staff understand responsible AI use, data handling, and internal policies. Relying solely on the cloud provider does not satisfy the customer's shared responsibility for AI governance, governance should involve more than just developers, and waiting for user-reported issues is reactive rather than responsible governance.
Question 4
A company wants to establish a data governance framework for its AI system. The framework must give the company the ability to monitor when data is generated, updated, and scheduled for deletion.
Which data governance component meets these requirements?
A. Data residency
B. Data lifecycle management
C. Data observability
D. Data logging
Show Answer
Correct Answer: B
Explanation: Data lifecycle management governs data throughout its lifecycle, including creation, updates, retention, archival, and scheduled deletion. It provides policies and processes to monitor and manage data from generation through disposal. Data residency concerns where data is stored, data observability focuses on data health and quality, and data logging records events but does not govern the full lifecycle.
Question 5
A company is training a foundation model (FM). The company wants the FM training data to be well managed, secure, and compliant throughout the data lifecycle. The data must follow governance practices.
Which option is an AWS data governance strategy for managing data across the data lifecycle?
A. Allow unrestricted access to all data for every employee.
B. Store data indefinitely without classification or retention policies.
C. Rely solely on manual reviews for data quality and compliance.
D. Establish data lifecycle policies, access controls, logging, and monitoring.
Show Answer
Correct Answer: D
Explanation: AWS data governance emphasizes managing data throughout its lifecycle with defined lifecycle policies, least-privilege access controls, auditing through logging, and continuous monitoring to support security, compliance, and governance. The other options contradict governance best practices by removing controls, omitting retention/classification, or relying only on manual processes.
Question 6
A company needs to document an ML model's purpose, owners, and limitations.
Which AWS service or feature provides this capability?
A. Amazon Bedrock
B. AWS AI Service Cards
C. AWS Prescriptive Guidance
D. Amazon SageMaker Model Cards
Show Answer
Correct Answer: D
Explanation: Amazon SageMaker Model Cards are designed to document machine learning models, including their intended purpose, owners, limitations, intended use, performance, and risk information to support governance and responsible AI practices.
Question 7
A company needs to evaluate AI-generated summaries against reference text. The company must measure semantic similarity and coverage of key information.
Which metrics meet these requirements? (Choose two.)
A. F1 score
B. BERTScore
C. Bilingual Evaluation Understudy (BLEU) score
D. Accuracy
E. Recall-Oriented Understudy for Gisting Evaluation (ROUGE)
Show Answer
Correct Answer: B, E
Explanation: BERTScore measures semantic similarity using contextual embeddings, making it suitable for evaluating meaning rather than exact token overlap. ROUGE measures overlap with the reference text, particularly recall, making it well suited for assessing coverage of key information in summaries.
Question 8
A human resources company is building an AI/ML solution to screen resumes and select relevant applicants for various job roles.
Which AI methodologies will help ensure impartial treatment for all demographic groups? (Choose two.)
A. Modularity
B. Fairness
C. Explainability
D. Secrecy
E. Underfitting
Show Answer
Correct Answer: B, C
Explanation: Fairness is the primary AI principle used to reduce bias and help ensure equitable treatment across demographic groups. Explainability complements fairness by making model decisions understandable and auditable, helping identify and address potential discriminatory behavior. Modularity, secrecy, and underfitting do not directly ensure impartial treatment.
Question 9
An AI practitioner is developing a recommendation system. The AI practitioner wants to document a business problem, data assumptions, training considerations, and usage risks. The company must follow guidelines for transparency and governance.
Which Amazon SageMaker AI feature will meet these requirements?
A. Model Registry
B. Model Cards
C. Model Monitor
D. Model Dashboard
Show Answer
Correct Answer: B
Explanation: Amazon SageMaker Model Cards provide standardized documentation for ML models, including the business problem, intended use, data assumptions, training details, evaluation, limitations, and usage risks to support transparency and governance.
Question 10
Which benefit does a company gain by using ongoing pre-training to fine-tune a foundation model (FM)?
A. Decreased model complexity
B. Improved model performance over time
C. Decreased time required to train the model
D. Reduced model training cost
Show Answer
Correct Answer: B
Explanation: Ongoing pre-training continues adapting a foundation model with additional data, allowing it to incorporate new patterns and knowledge, which improves performance over time. It does not inherently decrease model complexity, reduce training time, or lower training costs; in fact, ongoing training generally requires additional compute and expense.
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