Free AWS AI Practitioner Practice Test 2026 — AIF-C01 Exam Questions
Master the AWS Certified AI Practitioner (AIF-C01) exam with 600+ free practice questions covering all 4 AWS CAIP study domains. Each question includes a detailed explanation with AWS service context — no signup required.
AWS Certified AI Practitioner Exam Overview
- Questions: 65 (50 scored + 15 unscored), multiple-choice and multiple-response
- Time: 90 minutes
- Passing score: 700 / 1000
- Cost: $100 USD
- Validity: 3 years (recertify by passing AIF-C01 again or any Associate / Professional / Specialty exam)
Practice by AWS CAIP Domain
Domain 1: AWS AI Services (~28%)
Free AIF-C01 practice questions on Amazon Bedrock, SageMaker, Amazon Q, Rekognition, Comprehend, Textract, Polly, Transcribe, Translate, Lex, and Personalize. Practice this domain →
Domain 2: Machine Learning Fundamentals (~27%)
Free AIF-C01 practice questions on supervised / unsupervised / reinforcement learning, deep learning, foundation models, LLMs, prompt engineering, RAG, fine-tuning, model evaluation, and responsible AI. Practice this domain →
Domain 3: Data Engineering for AI (~22%)
Free AIF-C01 practice questions on S3 data lakes, AWS Glue, Athena, Lake Formation, SageMaker Ground Truth, Data Wrangler, Feature Store, and vector databases. Practice this domain →
Domain 4: Model Deployment and Operations (~23%)
Free AIF-C01 practice questions on SageMaker endpoints, Bedrock Guardrails, MLOps pipelines, model monitoring, SageMaker Clarify, IAM, KMS, and compliance for AI workloads. Practice this domain →
8 Free AWS AI Practitioner Sample Questions with Answers
Each question below includes 4 answer options, the correct answer, and a detailed explanation. These are real questions from the FlashGenius AIF-C01 question bank.
Sample Question 1 — AWS AI Services
A retail company wants to analyze customer reviews to determine the overall sentiment and categorize them by product feature. Which AWS service should they use to efficiently perform sentiment analysis and entity recognition?
- A. Amazon Comprehend (Correct answer)
- B. Amazon Rekognition
- C. Amazon Lex
- D. Amazon Polly
Correct answer: A
Explanation: Amazon Comprehend is designed for natural language processing tasks, including sentiment analysis and entity recognition. Amazon Rekognition is for image and video analysis, Amazon Lex is for building conversational interfaces, and Amazon Polly is for text-to-speech conversion.
Sample Question 2 — AWS AI Services
A financial institution needs to automate the extraction of data from scanned documents to streamline their loan processing. Which AWS service is most appropriate for this task?
- A. Amazon Textract (Correct answer)
- B. Amazon Rekognition
- C. Amazon Translate
- D. Amazon SageMaker
Correct answer: A
Explanation: Amazon Textract is specifically designed to extract text and data from scanned documents. Amazon Rekognition focuses on image and video analysis, Amazon Translate is for language translation, and Amazon SageMaker is for building, training, and deploying machine learning models.
Sample Question 3 — Data Engineering for AI
A retail company wants to analyze customer reviews to identify key themes and sentiments about their products. Which AWS service is best suited for this task?
- A. Amazon Rekognition
- B. Amazon Comprehend (Correct answer)
- C. Amazon Polly
- D. Amazon SageMaker
Correct answer: B
Explanation: Amazon Comprehend is designed for natural language processing tasks such as sentiment analysis and entity recognition. Amazon Rekognition is for image and video analysis, Amazon Polly is for text-to-speech, and Amazon SageMaker is for building and deploying machine learning models.
Sample Question 4 — Data Engineering for AI
A financial firm needs to detect fraudulent transactions in real-time. Which AWS service can help them deploy a machine learning model for this use case?
- A. Amazon SageMaker (Correct answer)
- B. AWS Glue
- C. Amazon Lex
- D. Amazon Translate
Correct answer: A
Explanation: Amazon SageMaker is a fully managed service that provides tools to build, train, and deploy machine learning models quickly. AWS Glue is for ETL, Amazon Lex is for building conversational interfaces, and Amazon Translate is for language translation.
Sample Question 5 — Machine Learning Fundamentals
Your company needs to build a real-time recommendation system for your e-commerce website. Which AWS service should you use to implement this solution efficiently?
- A. Amazon Comprehend
- B. Amazon SageMaker
- C. Amazon Personalize (Correct answer)
- D. Amazon Rekognition
Correct answer: C
Explanation: Amazon Personalize is specifically designed for building personalized recommendation systems. Amazon Comprehend is used for natural language processing, Amazon SageMaker is a general-purpose machine learning service, and Amazon Rekognition is for image and video analysis.
Sample Question 6 — Machine Learning Fundamentals
A healthcare company wants to extract insights from unstructured text data in medical records. Which AWS service would be most appropriate for this task?
- A. Amazon Rekognition
- B. Amazon Comprehend Medical (Correct answer)
- C. Amazon SageMaker
- D. Amazon Lex
Correct answer: B
Explanation: Amazon Comprehend Medical is designed for extracting information from unstructured medical text. Amazon Rekognition is for image analysis, Amazon SageMaker is a general-purpose machine learning platform, and Amazon Lex is for building conversational interfaces.
Sample Question 7 — Model Deployment and Operations
A retail company wants to deploy a machine learning model to predict customer churn. They require a service that allows easy deployment with built-in monitoring and automatic scaling. Which AWS service should they use?
- A. Amazon SageMaker (Correct answer)
- B. AWS Lambda
- C. Amazon Comprehend
- D. Amazon Rekognition
Correct answer: A
Explanation: Amazon SageMaker provides a fully managed service to deploy machine learning models with built-in capabilities for monitoring and automatic scaling. AWS Lambda is not suited for model deployment, while Amazon Comprehend and Amazon Rekognition are specific to text and image processing, respectively.
Sample Question 8 — Model Deployment and Operations
A healthcare startup needs to deploy a machine learning model that processes sensitive patient data. Which AWS feature should they consider to ensure compliance with data privacy regulations?
- A. Amazon SageMaker Model Monitor
- B. AWS Key Management Service (KMS) (Correct answer)
- C. Amazon Rekognition
- D. AWS CloudTrail
Correct answer: B
Explanation: AWS Key Management Service (KMS) helps manage encryption keys and ensure data is encrypted at rest and in transit, which is crucial for compliance with data privacy regulations. SageMaker Model Monitor is for model performance monitoring, Rekognition is for image analysis, and CloudTrail is for logging API calls.
Quick 10-Question AWS AI Practitioner Practice Test
Take a free 10-question AWS AI Practitioner quick-start practice test covering all 4 AIF-C01 domains. Get instant scoring with detailed explanations — perfect for a quick readiness check.
Why Choose FlashGenius for AWS AI Practitioner Prep?
Detailed explanations
Every question includes an explanation that connects the correct answer to AWS services such as Amazon Bedrock, SageMaker, Amazon Q, and the pre-built AWS AI services.
Domain-level practice
Practice and track progress across AWS AI Services, Machine Learning Fundamentals, Data Engineering for AI, and Model Deployment and Operations.
AIF-C01 blueprint coverage
The study questions cover the knowledge areas described in the AWS Certified AI Practitioner exam guide, including AI and ML fundamentals, generative AI, AWS AI services, responsible AI, and security.
Recommended AIF-C01 Study Plan
Combine the AWS Skill Builder AI Practitioner learning plan, hands-on practice with Bedrock and SageMaker, and timed FlashGenius practice tests.
2-Week Sprint Plan
- Days 1–3: Review machine learning and generative AI fundamentals, then take the Machine Learning Fundamentals domain test.
- Days 4–7: Study Bedrock, SageMaker, Amazon Q, and the pre-built AWS AI services. Use Bedrock playgrounds for hands-on practice.
- Days 8–11: Review data engineering, security, responsible AI, model deployment, and operations. Take both related domain tests.
- Days 12–14: Complete two full-length, timed mock exams and review every incorrect or guessed answer.
4-Week Standard Plan
- Week 1 — AI / ML and generative AI fundamentals: Complete the AWS Skill Builder AI Practitioner learning-plan modules on ML basics and generative AI. Take the FlashGenius Machine Learning Fundamentals domain test.
- Week 2 — AWS AI services deep dive: Study Amazon Bedrock, SageMaker, Amazon Q, and the pre-built AWS AI services. Use Bedrock playgrounds and SageMaker JumpStart for hands-on practice.
- Week 3 — Data engineering, security, and responsible AI: Review AWS Glue, S3 data lakes, SageMaker Ground Truth, Bedrock Guardrails, IAM, KMS, and SageMaker Clarify. Take the Data Engineering and Model Deployment domain tests.
- Week 4 — Mock exams and exam-day preparation: Take two or three full-length 65-question mock exams under timed conditions. Review every incorrect or guessed answer and aim for 80%+ on at least two mocks before scheduling.
AWS AI Practitioner vs Other Cloud / AI Certifications
AIF-C01 is a foundational certification focused on AI, machine learning, and generative AI services on AWS. AWS Cloud Practitioner covers broader cloud fundamentals, while associate-level certifications such as AWS Solutions Architect Associate and AWS Machine Learning Engineer Associate test deeper implementation skills.
| Certification | Level | Primary focus | List price | Validity |
|---|
| AWS AI Practitioner (AIF-C01) | Foundational | AI, ML, and generative AI on AWS | $100 USD | 3 years |
| AWS Cloud Practitioner (CLF-C02) | Foundational | General AWS cloud fundamentals | $100 USD | 3 years |
| AWS Solutions Architect Associate (SAA-C03) | Associate | Designing AWS solutions | $150 USD | 3 years |
| AWS Machine Learning Engineer Associate (MLA-C01) | Associate | Building and operating ML workloads | $150 USD | 3 years |
| Azure AI Fundamentals (AI-900) | Fundamentals | AI and ML on Microsoft Azure | Varies by region | Does not expire |
Prices are standard USD list prices and may vary by country, taxes, or current vendor policy.
AWS AI Practitioner Exam Day — What to Expect
- Format: 65 multiple-choice or multiple-response questions, including unscored questions.
- Length: 90 minutes.
- Passing score: 700 on AWS's 100–1000 scaled-score system.
- Delivery: Online proctored or at an authorized testing center.
- Retake policy: Candidates who do not pass must wait 14 days before another attempt and pay the exam fee again.
AWS AI Practitioner Careers and Salary Considerations
AIF-C01 is a foundational credential rather than a guarantee of a particular salary. Its value is strongest when combined with practical AWS, Bedrock, SageMaker, cloud, data, product, or consulting experience. Compensation varies substantially by role, location, seniority, and hands-on skills.
AWS AI Practitioner FAQs
Answers to common questions about exam cost, passing score, preparation time, retakes, certification validity, career paths, and study resources.
What is the AWS Certified AI Practitioner (AIF-C01) exam?
AWS Certified AI Practitioner (AIF-C01) is a foundational-level AWS certification that validates knowledge of AI, ML, and generative AI concepts and the AWS services that implement them — including Amazon Bedrock, SageMaker, and Amazon Q.
What score is needed to pass AWS AI Practitioner?
AWS uses a scaled score from 100 to 1000 with a passing score of 700. Aim for 75%+ on practice tests for a comfortable margin on exam day.
How much does the AWS AI Practitioner exam cost?
The AWS AI Practitioner (AIF-C01) exam fee is $100 USD via Pearson VUE or PSI — taken either online with a remote proctor or in person at a testing center. AWS occasionally offers exam discount vouchers via AWS re/Start, AWS Educate, and AWS Skill Builder.
How long should I study for AWS AI Practitioner?
Most candidates pass AIF-C01 in 2–4 weeks of focused study. Combine the free AWS Skill Builder AI Practitioner learning plan, hands-on time with Bedrock and SageMaker, and timed practice tests. 30–60 minutes a day works well for most.
Are these AWS AI Practitioner practice tests free?
Yes. FlashGenius offers free AWS AI Practitioner sample tests by domain plus a 10-question quick-start mock exam — no signup required. Premium unlocks the full 600+ question bank with full-length mocks and analytics.
What are the AWS AI Practitioner exam domains?
FlashGenius organizes the AWS CAIP question bank into 4 study domains: AWS AI Services (~28%), Machine Learning Fundamentals (~27%), Data Engineering for AI (~22%), and Model Deployment and Operations (~23%). These map to the official AWS AIF-C01 blueprint covering AI/ML fundamentals, generative AI, AWS AI services, responsible AI, and security/compliance.
How long is the AWS AI Practitioner certification valid?
The AWS Certified AI Practitioner certification is valid for 3 years. Recertification is via passing the current version of the exam or any AWS Associate, Professional, or Specialty exam.
AWS AI Practitioner vs AWS Cloud Practitioner — which should I take first?
AWS Cloud Practitioner (CLF-C02) covers general AWS cloud fundamentals — services, pricing, security, and architecture. AWS AI Practitioner (AIF-C01) focuses specifically on AI, ML, and generative AI services on AWS. If you're new to AWS, take CLF-C02 first; if you already know AWS basics and want to specialize in AI, jump straight into AIF-C01.
Do I need coding experience for AWS AI Practitioner?
No. AIF-C01 is conceptual — it focuses on what AWS AI services do, when to use them, and the responsible-AI guardrails around them. There are no coding questions. Basic familiarity with cloud computing and ML terminology helps, but no programming is required.
Is AWS AI Practitioner worth it in 2026?
Yes. AIF-C01 is one of the fastest-growing AWS certifications because organizations are rapidly adopting generative AI. It can demonstrate foundational AI literacy for cloud, data, product, and consulting roles and provides a starting point for role-based AWS AI and ML certifications.
Is the AWS AI Practitioner exam hard?
AIF-C01 is considered moderate among AWS Foundational certifications — easier than Associate-level certifications but broader in AI and ML terminology than Cloud Practitioner. Candidates with prior AWS or ML exposure may need 1–2 weeks; those new to both should plan 3–4 weeks.
What is the AWS AI Practitioner retake policy?
If you fail AIF-C01, you must wait 14 days before your next attempt. There is no limit on the total number of attempts, but each retake requires paying the full $100 USD exam fee.
What's the next AWS certification after AI Practitioner?
Common next steps include AWS Certified Machine Learning Engineer Associate (MLA-C01) for hands-on ML engineering or AWS Solutions Architect Associate (SAA-C03) for general cloud architecture. Choose the path that best matches your role and hands-on experience.
What are the best free AWS AI Practitioner study resources?
AWS Skill Builder has a free Standard Plan with the official AWS AI Practitioner learning plan. Pair it with the official AIF-C01 exam guide, AWS Bedrock and SageMaker workshops on AWS Workshop Studio, and independent practice tests such as the FlashGenius AIF-C01 sample sets on this page.
What is the average salary with an AWS AI Practitioner certification?
AIF-C01 is a foundational credential, so compensation depends primarily on role, location, experience, and hands-on AWS skills. Combined with practical Bedrock, SageMaker, cloud, or data experience, it can support progression into AI engineering, consulting, product, and architecture roles.
Free AWS AI Practitioner Cheat Sheet
Download the free AWS AI Practitioner cheat sheet — a one-page summary of every AIF-C01 domain covering Bedrock, SageMaker, responsible AI, and security at a glance.
Start the free AIF-C01 quick-start practice test now | AWS AI Practitioner Cheat Sheet | Get premium AIF-C01 question bank