Free AIF-C01 Practice Test | 400 Realistic exam questions 2026

What Is the AIF-C01 Exam?

AIF-C01 is the exam code for AWS Certified AI Practitioner, a foundational A Free IT certification practice testsWS certification. It is designed for people who want to show that they understand artificial intelligence, machine learning, generative AI, foundation models, and the AWS tools used for common AI solutions. Find Free IT certification practice tests.

This is not a coding-heavy machine learning engineering exam. AWS describes the intended candidate as someone who uses or works with AI/ML technology but does not necessarily build AI/ML solutions. The official guide recommends up to six months of exposure to AI/ML technologies on AWS. It also lists business analysts, IT support staff, marketing professionals, product and project managers, sales professionals, and line-of-business or IT managers as example roles. AWS Certified AI Practitioner exam page

The exam checks whether you can recognize the right AI approach for a business need, understand what a service can and cannot do, compare foundation-model options, identify responsible-AI risks, and choose sensible security and governance controls. You are not expected to develop algorithms, perform hyperparameter tuning, build ML pipelines, or complete advanced statistical analysis. Official AIF-C01 exam guide

Who Should Use This AIF-C01 Practice Test?

This practice test is useful if you are new to AI on AWS or work near an AI project without being the person who trains the models. You may be choosing a service, discussing requirements, reviewing costs, helping users, supporting governance, or explaining an AI solution to a customer or manager.

It is a good fit for:

• Business analysts who translate business needs into technology requirements.
• Cloud and IT support staff who need a clear view of AWS AI services.
• Product or project managers working with AI teams.
• Sales and marketing professionals discussing AI use cases with customers.
• Students exploring cloud, AI, or machine learning careers.
• AWS Cloud Practitioner holders who want to focus on AI and generative AI.
• Technical professionals who need a foundation before moving toward AWS Machine Learning Engineer – Associate.

There is no required course or prior certification. If AWS terms such as Regions, IAM, S3, Lambda, pricing, and the shared responsibility model are completely new to you, learn those basics first. AWS recommends Cloud Practitioner Essentials or AWS Technical Essentials for candidates who are new to both IT and AWS Cloud.

What an AIF-C01 Practice Test Should Help You Learn

A useful practice test does not reward memorizing answer positions. It helps you connect a business problem to the right concept or AWS service.

For example, you should be able to explain why classification fits a yes-or-no prediction, why clustering can group unlabeled data, why Amazon Transcribe converts speech to text, why Amazon Bedrock is used to build with foundation models, and why Retrieval Augmented Generation can ground a model response in approved business information.

Your practice sessions should help you:

• Measure your starting point. Take a mixed test before studying so you know which domains need the most work.
• Recognize decision words. Look for requirements involving cost, latency, accuracy, privacy, explainability, safety, or speed to market.
• Separate similar concepts. Know the difference between AI, ML, deep learning, generative AI, foundation models, and agentic AI.
• Connect services to use cases. Learn what each major AWS AI service is for instead of memorizing a long product list.
• Review responsible AI. Understand bias, fairness, transparency, explainability, hallucination, and human oversight.
• Improve exam pacing. With 65 questions in 90 minutes, you have about 83 seconds per question on average.

A practice-test score is not an official AWS score conversion. A better readiness sign is stable performance on fresh, mixed questions and the ability to explain why the wrong options fail. As a practical, unofficial target, many students aim to score at least 80 percent on new timed sets before booking, but understanding the explanations matters more than reaching a number on a familiar test.

AIF-C01 Exam Domains and Topic Weightings

The current AIF-C01 blueprint has five scored domains. Use the percentages to divide your study time, but do not ignore the smaller domains. Together, responsible AI and security, compliance, and governance account for 28 percent of scored content—the same weight as the largest individual domain.

Domain 1: Fundamentals of AI and ML — 20%

This domain checks whether you understand basic terms, useful AI applications, and the AI/ML development lifecycle. Study the differences between supervised, unsupervised, and reinforcement learning. Know common tasks such as regression, classification, clustering, natural language processing, computer vision, forecasting, recommendation, and fraud detection.

You should also understand labeled and unlabeled data, structured and unstructured data, training and inference, overfitting and underfitting, and metrics such as accuracy, precision, recall, and F1 score. The goal is not to calculate complex formulas. The goal is to recognize which metric or approach makes sense for the situation.

Practice questions may ask when AI is not the right choice. A fixed rules engine can be better when the result must always be exact and predictable. An AI solution also needs a clear business benefit that justifies data, development, operation, and monitoring costs. 

Domain 2: Fundamentals of Generative AI — 24%

Domain 2 covers the building blocks of generative AI. Learn tokens, embeddings, vectors, chunking, transformers, foundation models, multimodal models, diffusion models, prompt engineering, and the foundation-model lifecycle.

You should be able to match generative AI to practical tasks such as summarization, translation, code generation, image creation, search, recommendations, customer-service assistants, and content drafting. You must also recognize limitations, including hallucinations, nondeterministic output, poor explainability, bias, and inaccurate responses.

The current guide includes agentic-AI concepts. Study what agents do, how tools let an agent act on an external system, how memory can preserve useful context, and how workflows coordinate tasks. Understand at a high level that Model Context Protocol, or MCP, can connect agents with external tools and data. You do not need to write an MCP server for this foundational exam.

Also review how token usage affects cost, and how model choice can affect latency, regional availability, accuracy, compliance, and price.

Domain 3: Applications of Foundation Models — 28%

This is the largest domain. Expect questions about selecting, prompting, customizing, and evaluating foundation models.

When comparing models, consider modality, response quality, context length, latency, cost, multilingual support, customization needs, and model size. Learn how temperature influences variation in an output and why longer input or output can increase token cost.

Retrieval Augmented Generation, usually shortened to RAG, deserves special attention. RAG retrieves relevant information from an approved source and adds it to the model context before a response is generated. It can improve grounding and make a model more useful with current company knowledge without fully retraining the model. Know that vector databases can store embeddings and that AWS options include Amazon OpenSearch Service and supported databases such as Amazon Aurora and Amazon RDS for PostgreSQL.

Prompt questions may cover zero-shot, single-shot, few-shot, context, instructions, prompt templates, negative prompts, guardrails, and prompt versioning. Learn the risks too: prompt injection, prompt poisoning, jailbreaking, and accidental exposure of sensitive information.

Finally, compare pre-training, fine-tuning, continuous pre-training, distillation, in-context learning, and RAG at a basic decision level. Review human evaluation, benchmark datasets, business metrics, and model-evaluation services. Domain 3 objectives

Domain 4: Guidelines for Responsible AI — 14%

Responsible AI is about building and using AI in a way that is fair, safe, transparent, inclusive, robust, and trustworthy. Practice identifying biased datasets, unbalanced representation, unsafe outputs, hallucinations, intellectual-property risks, and situations that require human review.

Understand the difference between transparency and explainability. Transparency provides useful information about how a model was created and used. Explainability helps people understand why a model produced a result. Some highly accurate models can be harder to interpret, so a question may ask you to balance performance with legal, safety, or business needs.

AWS tools and features named in this area include Amazon Bedrock Guardrails, SageMaker Clarify, SageMaker Model Monitor, SageMaker Model Cards, Amazon Augmented AI, and Amazon Bedrock Model Evaluation. Focus on the problem each tool addresses. Domain 4 objectives

Domain 5: Security, Compliance, and Governance for AI Solutions — 14%

This domain connects AI to familiar cloud-security principles. Study least-privilege access with AWS Identity and Access Management, encryption at rest and in transit, private connectivity, data access control, data integrity, logging, monitoring, and the AWS shared responsibility model.

AI-specific risks include prompt injection, sensitive-data leakage, toxic output, insecure agents, weak output validation, and missing audit trails. Grounding, confidence scoring, output filtering, and human review can reduce some risks, but no control makes every model response automatically correct.

For governance, review data lineage, residency, retention, monitoring, review schedules, policies, staff training, and documentation. Know the general purpose of AWS CloudTrail, AWS Config, AWS Audit Manager, AWS Artifact, Amazon Macie, AWS KMS, and AWS Trusted Advisor. Domain 5 objectives

AWS Services to Recognize for AIF-C01

Do not try to memorize every service on the official in-scope list in one sitting. Start with service-to-task pairs:

• Amazon Bedrock: Build generative-AI applications with foundation models; also review Knowledge Bases, Guardrails, Prompt Management, Agents, and Model Evaluation.
• Amazon SageMaker AI: Build, train, deploy, and monitor ML models across the ML lifecycle.
• SageMaker JumpStart: Access pretrained models, solution templates, and starting points for ML work.
• Amazon Q: Generative-AI assistance for supported business and developer tasks.
• Amazon Comprehend: Extract meaning and insights from text.
• Amazon Lex: Build conversational interfaces.
• Amazon Polly: Convert text to speech.
• Amazon Transcribe: Convert speech to text.
• Amazon Translate: Translate text between languages.
• Amazon Rekognition: Analyze images and video.
• Amazon Textract: Extract text and structured data from documents.
• Amazon Personalize: Build personalized recommendations.
• Amazon Kendra: Intelligent enterprise search.

The official list is non-exhaustive and can change. Check the current AIF-C01 in-scope AWS services during your final review. View all AWS practice tests.

How to Use the AIF-C01 Practice Test Properly

Step 1: Take a baseline test

Answer a mixed set without notes or web searches. Do not worry if the first score is low. The purpose is to show where to begin.

Step 2: Review every explanation

Review correct answers as well as mistakes. A lucky guess hides a knowledge gap. For each question, write down the tested concept, the deciding clue, and why the other choices do not fit.

Step 3: Build an error log

Create five headings, one for each exam domain. Put every missed or guessed concept under the right heading. Be specific: write “precision versus recall” or “RAG versus fine-tuning,” not simply “AI.”

Step 4: Study the concept in an official source

Use the exam guide and AWS service documentation to correct the gap. A short service demo can make abstract terms easier to remember, even though advanced hands-on building is outside the exam’s expected job tasks.

Step 5: Retake with new questions

Repeating the same set measures memory. New questions measure understanding. Use fresh domain sets first, then return to full-length mixed tests.

Step 6: Simulate the real exam

Set a 90-minute timer, close notes, silence your phone, and answer all 65 questions in one sitting. Flag slow questions and return after completing the easier ones.

Four-Week AIF-C01 Study Plan

Week 1: AI and ML foundations

Take a baseline test. Study AI, ML, deep learning, generative AI, agentic AI, data types, supervised learning, unsupervised learning, reinforcement learning, and common business use cases. Finish with a Domain 1 quiz.

Week 2: Generative AI and AWS services

Study tokens, embeddings, vectors, foundation models, multimodal models, the FM lifecycle, and token-based pricing. Build a service-to-use-case table for Bedrock, SageMaker AI, Q, Comprehend, Lex, Polly, Transcribe, Translate, Rekognition, and Textract. Complete Domain 2 questions.

Week 3: Foundation-model applications

Focus on Domain 3. Compare RAG, fine-tuning, in-context learning, and pre-training. Practise model-selection scenarios, prompt techniques, prompt risks, agents, vector databases, and evaluation metrics. Take one mixed timed test at the end of the week.

Week 4: Responsible AI, security, and final review

Study bias, fairness, explainability, privacy, IAM, encryption, governance, compliance, logging, and human oversight. Review your error log, then complete two fresh timed simulations on different days. Use the final day for light review rather than cramming.

AIF-C01 Exam Administration

The exam is administered through Pearson VUE. Your AWS Certification Account is separate from the AWS account used for cloud services. To schedule the exam:

1. Sign in to your AWS Certification Account.
2. Select Schedule New Exam.
3. Find AWS Certified AI Practitioner (AIF-C01).
4. Select Schedule with Pearson VUE.
5. Choose online or test-center delivery, select an appointment, and pay by card or an eligible voucher.
6. Read the confirmation email and check the identification rules.

You may cancel or reschedule at least 24 hours before the appointment. An appointment can be rescheduled no more than twice. A late cancellation or missed appointment normally results in loss of the exam fee. If you fail, AWS requires a 14-calendar-day wait before another attempt, and you must pay the full registration fee again. Detailed results are normally available in your AWS Certification Account within five business days. AWS Certification FAQs and scheduling policies

Candidates with approved accessibility needs must request accommodations before scheduling. Non-native English speakers taking the exam in English can request the ESL +30 accommodation, which adds 30 minutes. AWS accommodations and scheduling guidance

Is the AIF-C01 Exam Online?

You can take AIF-C01 as an online proctored exam through Pearson VUE or at a Pearson VUE testing center.

For online testing, use the same computer and internet connection to run the required system test before exam day. You need a working webcam, microphone, speakers, a supported operating system, and a private, quiet room. Your desk must be clear, and no one else can enter or view your screen.

Online check-in begins 30 minutes before the appointment and includes technology checks, photos of you and your ID, and a room scan. Your valid government-issued photo ID must match the name on the booking. Online candidates cannot leave the webcam view for a break during the exam. Pearson VUE AWS online testing rules

Choose a test center if your connection is unstable, your device is managed by an employer, or you cannot guarantee a private room. Choose online testing if you have reliable equipment, a quiet space, and can follow the room and desk rules for the full session.

Common AIF-C01 Preparation Mistakes

• Memorizing AWS service names without learning their use cases.
• Treating AIF-C01 as only an Amazon Bedrock exam.
• Ignoring responsible AI, security, and governance because they seem less technical.
• Confusing generative AI with all machine learning.
• Assuming a model is always better when it is larger or more expensive.
• Mixing up RAG, fine-tuning, and prompt engineering.
• Repeating one practice set until the answers become familiar.
• Leaving questions unanswered even though AWS applies no guessing penalty.
• Studying from an old outline that omits ordering, matching, agentic AI, or MCP.
• Using unauthorized “real questions” instead of objective-based practice.

AIF-C01 Test-Day Checklist

• Confirm the appointment time and time zone.
• Check that your account name matches your identification.
• Run the online system test again if you are testing remotely.
• Prepare a clear desk and private room, or confirm the test-center route and travel time.
• Arrive or begin check-in 30 minutes early.
• Read each question for cost, security, latency, accuracy, and business requirements.
• Flag difficult questions and return later.
• Select every required answer in multiple-response questions.
• Complete every item because unanswered questions are incorrect.
• Save the last few minutes for incomplete or flagged items.

Frequently Asked Questions About AIF-C01

How many questions are on the AIF-C01 exam?

There are 65 questions. The official guide states that 50 affect your score and 15 are unscored. The unscored items are not identified.

How long is the AWS AI Practitioner exam?

The exam time is 90 minutes. The optional ESL +30 accommodation gives eligible non-native English speakers an additional 30 minutes when testing in English.

What score do I need to pass AIF-C01?

You need a scaled score of 700 on a 100–1,000 scale. This is not a simple percentage conversion.

How much does AIF-C01 cost?

The base price is USD $100. Taxes, exchange rates, and local pricing may change the final amount shown during scheduling.

Do I need coding experience for AIF-C01?

No. Coding models, tuning hyperparameters, building ML pipelines, and advanced statistical work are outside the expected job tasks. Basic AWS and AI familiarity is still helpful.

Is AWS Cloud Practitioner required before AIF-C01?

No. There is no certification prerequisite. Cloud Practitioner can help if you are completely new to AWS, but candidates who already understand basic AWS services, IAM, pricing, and shared responsibility can prepare directly for AIF-C01.

Is AIF-C01 difficult?

It can be challenging for beginners because many terms and AWS services sound similar. The depth is foundational, but the exam still expects you to choose the best answer for a business scenario. Domain-based practice and clear service comparisons make the material more manageable.

Can an AIF-C01 practice test guarantee a pass?

No. A practice test can measure progress, reveal gaps, and improve timing, but no provider can guarantee an official result. Combine practice questions with the current AWS exam guide, official training, and targeted review.

How long is AWS Certified AI Practitioner valid?

The certification is valid for three years. AWS states that you can recertify by passing the latest version of the exam or by earning AWS Certified Machine Learning Engineer – Associate, which automatically recertifies AI Practitioner. AWS AI Practitioner validity and next steps

What should I do the day before the exam?

Review your error log, service-to-use-case notes, and the five domain weights. Confirm your ID, appointment, testing location, and online system check. Avoid starting a new course or taking several full tests. Rest and begin check-in early, Explore Online Learning Resources