Free AIF-C01: AWS Certified AI Practitioner Exam Questions and Answers
AWS Certified AI Practitioner (AIF-C01) is the foundational AWS exam for people who use AI and machine learning services rather than build them — AWS pitches it at candidates with up to six months of exposure to AI/ML on AWS, and there is no prerequisite. It runs 90 minutes, costs $100 and asks 65 questions, 50 scored and 15 unscored; formats are multiple choice, multiple response, ordering and matching. Scoring is scaled 100–1,000 with 700 to pass, compensatory across domains, and the credential is valid for three years.
Five domains are weighted: fundamentals of AI and ML 20%, fundamentals of generative AI 24%, applications of foundation models 28%, responsible AI 14%, and security, compliance and governance 14% — over half the marks sit in generative AI and foundation models, where the Amazon Bedrock, prompt-engineering and model-selection questions cluster.
Candidates comparing AIF-C01 exam dumps, ExamTopics and other AIF-C01 practice tests use this page for the answers and explanations behind each question. Download the free AIF-C01 PDF, then sit the timed AIF-C01 exam simulation before booking with Amazon.
Last updated: November 1, 2026
- Exam code
- AIF-C01
- Provider
- Amazon
- Questions in our bank
- 1000+
- Free to read
- First 10, with answers
- Our test mode duration & pass mark
- 130 mins · 70%
- Verified answers
- Reviewed weekly
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Question #1
A company stores customer support transcripts in an Amazon S3 bucket. The company plans to use the transcripts to fine-tune a foundation model (FM). Before fine-tuning, the company must find out whether any transcripts contain personally identifiable information (PII). Which AWS service will meet this requirement with the LEAST operational overhead?
Correct answer: D
Explanation
Amazon Macie uses machine learning and pattern matching to discover sensitive data such as PII in Amazon S3 objects, so it fits the data check before fine-tuning. GuardDuty detects threats and suspicious activity, not sensitive content. AWS Config tracks resource configuration, and Amazon Inspector scans for software vulnerabilities.
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Question #2
Which term describes a subset of machine learning that uses neural networks with many layers to learn patterns from data?
Correct answer: A
Explanation
Deep learning is the subset of machine learning built on multilayer (deep) neural networks. Reinforcement learning describes learning from rewards through interaction with an environment. Natural language processing is an application field and anomaly detection is a task, and neither defines a network architecture.
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Question #3
A company has customized a foundation model (FM) in Amazon Bedrock. The company will use the custom model for a steady, high-volume production workload that needs a guaranteed level of throughput. Which Amazon Bedrock option will meet these requirements?
Correct answer: C
Explanation
Provisioned Throughput buys dedicated model units for a model, which gives a fixed and guaranteed level of throughput for steady production traffic. Cross-Region inference spreads requests across Regions to handle bursts, but it does not reserve capacity. On-Demand mode bills per token with no throughput guarantee, and batch inference is for offline jobs, not steady real-time traffic.
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Question #4
A company wants to build a search feature that returns support articles with a similar meaning to a user's question, even when the articles and the question share no keywords. Which generative AI concept should the search feature use?
Correct answer: B
Explanation
Embeddings are numerical vectors that capture the semantic meaning of text. Texts with similar meaning sit close together in vector space, so the search can find matches without shared keywords. Tokenization only splits text into units for the model to process. Temperature and the context window affect text generation, not similarity search.
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Question #5
A healthcare company is building a generative AI assistant on Amazon Bedrock to answer patient questions about prescribed medications. The company wants to follow responsible AI practices during development. Which actions will meet these requirements? (Select TWO.)
Select 2 answers.
Correct answer: A, C
Explanation
Responsible AI development includes testing for fairness with prompts that represent the real patient population. It also includes human oversight of high-risk outputs such as dosage guidance. The provider's benchmarks do not reflect the company's own use case. Unvetted public forum posts can add inaccurate or biased content, and temperature controls randomness, not fairness.
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Question #6
A company wants to use a large language model (LLM) on Amazon Bedrock for sentiment analysis. The company wants to know how much information can fit into one prompt. Which consideration will inform the company's decision?
Correct answer: B
Explanation
The context window defines the maximum number of tokens a model can accept in a single prompt, so it determines how much information fits in one prompt. Temperature, batch size and model size do not set that limit.
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Question #7
A company is building a large language model (LLM) question answering chatbot. The company wants to decrease the number of actions call center employees need to take to respond to customer questions. Which business objective should the company use to evaluate the effect of the LLM chatbot?
Correct answer: B
Explanation
Average call duration directly measures whether agents need fewer actions and less time to resolve customer questions, so it is the right business metric for the chatbot's effect.
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Question #8
A law firm wants to build an AI application by using large language models (LLMs). The application will read legal documents and extract key points from the documents. Which solution meets these requirements?
Correct answer: C
Explanation
A summarization chatbot is ideal for extracting key points from legal documents. Large language models (LLMs) can be used to summarize complex texts, such as legal documents, making them more accessible and understandable. • Option C (Correct): "Develop a summarization chatbot": This is the correct answer because a summarization chatbot uses LLMs to condense and extract key information from text, which is precisely the requirement for reading and summarizing legal documents. • Option A: "Build an automatic named entity recognition system" is incorrect because it focuses on identifying specific entities, not summarizing documents. • Option B: "Create a recommendation engine" is incorrect as it is used to suggest products or content, not summarize text. • Option D: "Develop a multi-language translation system" is incorrect because translation is unrelated to summarizing text. AWS AI Practitioner References: • Using LLMs for Text Summarization on AWS: AWS supports developing summarization tools using its AI services, including Amazon Bedrock.
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Question #9
A company has developed an ML model for image classification. The company wants to deploy the model to production so that a web application can use the model. The company needs to implement a solution to host the model and serve predictions without managing any of the underlying infrastructure. Which solution will meet these requirements?
Correct answer: A
Explanation
SageMaker Serverless Inference hosts the model and serves predictions while AWS provisions and scales the compute automatically, so no infrastructure is managed. CloudFront, API Gateway and AWS Batch do not host ML models for inference.
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Question #10
A company has documents that are missing some words because of a database error. The company wants to build an ML model that can suggest potential words to fill in the missing text. Which type of model meets this requirement?
Correct answer: D
Explanation
BERT-based models are trained with a masked language modeling objective and use bidirectional context to predict missing words, which is exactly the fill-in-the-blank task described.
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Discussion
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FAQ
Learn More: https://aws.amazon.com/certification/
- Q1: What is the AIF-C01: AWS Certified AI Practitioner exam?
- A: AIF-C01: AWS Certified AI Practitioner is a Amazon certification exam. Judging by the questions in our bank, it concentrates on amazon, bedrock, sagemaker, chatbot and practitioner.
- Q2: What topics does the AIF-C01: AWS Certified AI Practitioner exam cover?
- A: Questions in our AIF-C01: AWS Certified AI Practitioner bank cluster around amazon, bedrock, sagemaker, chatbot, practitioner, models, meets and language. Working through the full set is the quickest way to find which of these you are weakest on.
- Q3: How should I prepare for AIF-C01: AWS Certified AI Practitioner?
- A: Work through the AIF-C01: AWS Certified AI Practitioner practice questions here, checking your answer on each one, then sit the practice test to rehearse the exam under timed conditions before the real thing.
- Q4: Are these real AIF-C01: AWS Certified AI Practitioner exam questions?
- A: They are drawn from officially released past questions and from community members who have sat AIF-C01: AWS Certified AI Practitioner. Answers are verified and updated weekly.
- Q5: Where do I register for the AIF-C01: AWS Certified AI Practitioner exam?
- A: Register through Amazon directly. Exampractice is not affiliated with Amazon and does not administer the exam.
- Q6: Is there a free AIF-C01: AWS Certified AI Practitioner sample?
- A: Yes. Every AIF-C01: AWS Certified AI Practitioner page shows a free sample of real questions. Upgrading opens the full bank and the practice test.
- Q7: What are Amazon Certification Exams?
- A: Amazon Certification Exams validate your expertise in Amazon Web Services (AWS), covering a range of cloud computing skills, including architecture, development, operations, and data analytics. These certifications demonstrate your proficiency in designing, deploying, and managing applications on the AWS platform.
- Q8: Why should I pursue Amazon Certification?
- A: Amazon Certification enhances your professional credibility, showcasing your skills and knowledge in AWS services. This can lead to better job opportunities, higher salaries, and career advancement in the cloud computing and IT industry.
- Q9: What are the benefits of Amazon Certification?
- A: Benefits include recognition as a certified cloud professional, improved job performance, access to exclusive resources, continuing education opportunities, and staying current with the latest AWS technologies and best practices.
- Q10: Who should take Amazon Certification Exams?
- A: IT professionals, cloud architects, developers, system administrators, data analysts, and anyone involved in designing, implementing, and managing cloud solutions on AWS should consider these certifications to validate their expertise and advance their careers.
- Q11: What types of Amazon Certification Exams are available?
- A: Amazon offers various certification paths, including Foundational Level (AWS Certified Cloud Practitioner), Associate Level (AWS Certified Solutions Architect, AWS Certified Developer, AWS Certified SysOps Administrator), Professional Level (AWS Certified Solutions Architect – Professional, AWS Certified DevOps Engineer – Professional), and Specialty Certifications (Security, Big Data, Advanced Networking, and more).
- Q12: How do I prepare for Amazon Certification Exams?
- A: Preparation can include official AWS training courses, study guides, practice exams, online tutorials, and hands-on experience with AWS services and solutions.
- Q13: Where can I take Amazon Certification Exams?
- A: Amazon Certification Exams can be taken online or at authorized testing centers worldwide, providing flexibility to fit your schedule and location.
- Q14: How do Amazon Certifications impact my career?
- A: Amazon Certifications significantly boost your career by demonstrating your expertise to employers, making you a more competitive candidate for advanced roles and promotions in the cloud computing and IT industry.
- Q15: Are there any prerequisites for Amazon Certification Exams?
- A: Some exams may have prerequisites, such as foundational knowledge or prior certifications. Check the specific requirements for each certification path on the AWS Certification website.
- Q16: How often do I need to recertify for Amazon Certifications?
- A: AWS Certifications typically require recertification every three years to ensure that certified professionals stay updated with the latest AWS technologies and industry practices.