AWS Certified AI Practitioner (AIF-C01) practice exam & study guide

AWS positions the AI Practitioner as proof that you understand AI/ML fundamentals, generative-AI concepts, how to apply foundation models (including prompt engineering and Retrieval Augmented Generation), and the guidelines for responsible, secure, and governed AI. It is vendor-focused — the emphasis is on AWS services such as Amazon Bedrock, Amazon Q, and SageMaker.

Like the Cloud Practitioner, it does not require you to build or train models. It checks that you can reason about when to use AI/ML, recognise the right AWS AI service for a scenario, and understand risks like bias and hallucination — enough to collaborate on AI initiatives.

By professional-certification standards AIF-C01 is considered easy-to-moderate: it is a foundational exam, the questions are recognition-based rather than hands-on, and there are no labs. Most candidates who study consistently for a few weeks pass comfortably.

The difficulty that exists comes from the breadth of generative-AI terminology and knowing which AWS AI service fits a use case — for example when to use Bedrock versus SageMaker, or RAG versus fine-tuning. Confident pattern-matching, not deep math, is what the exam rewards.

The live AIF-C01 exam contains 65 questions to be answered in 90 minutes — 50 scored plus 15 unscored questions AWS uses to trial future content — using a mix of question types: multiple choice, multiple response, ordering, and matching. Our full-length practice mock mirrors the length and timing with a 65-question, 90-minute timer.

You can sit the exam at a Pearson VUE test centre or online with proctoring from home.

AWS scores AIF-C01 on a scaled range of 100 to 1,000, and you need 700 to pass. The score is scaled rather than a simple percentage, and there are no per-domain pass marks — you need an overall 700. Our practice mock flags a pass at 70% to give you a comparable target.

The AIF-C01 exam costs 100 USD (prices vary by region), and the certification is valid for three years. Everything on this hub — questions, mock exams, glossary, and domain guides — is completely free.

The AI Practitioner is aimed at a broad audience: business analysts, product and project managers, salespeople, and IT professionals who work with AI-using teams, as well as engineers who want a foundation before role-based AI/ML certifications.

AWS recommends up to six months of exposure to AI/ML technologies on AWS, but no hands-on model-building experience is required — the exam is conceptual.

The AI Practitioner is relevant to roles that collaborate on AI initiatives — product managers, analysts, and technical staff adding AI literacy — and is a sensible foundation before the Machine Learning Engineer - Associate.

How much any certification moves compensation depends heavily on role, geography, and experience, so treat any single salary figure with caution. AIF-C01 is best viewed as a way to demonstrate AI fluency rather than a guaranteed raise on its own.

A candidate with some cloud or AI exposure can be ready in one to three weeks; a complete beginner should plan for four to six weeks at roughly an hour a day. Learn the concepts domain by domain, then switch to timed practice questions to get used to how AWS phrases scenarios.

A good rhythm is to study one domain at a time and drill its topic quiz immediately, then move to full-length mocks — reviewing every explanation, including for questions you answered correctly, because AIF-C01 distractors are built from plausible AI-service confusions.

Start by reading each domain above, then work the practice questions domain by domain. Every question on MockAPI reveals a full explanation and tells you why each wrong answer is wrong — the most valuable part on a concept-recognition exam.

When you can answer topic drills comfortably, move to a full-length timed mock to rehearse pacing, and use the glossary to close gaps in AI terminology. Aim to score consistently above the pass mark before you book.

Yes. You can sit AIF-C01 at a Pearson VUE testing centre or online from home with OnVUE remote proctoring, which requires a quiet private room, a stable connection, a webcam, and government-issued photo ID.

If you do not pass, AWS lets you retake after a 14-day waiting period, with no limit on attempts, though each attempt requires a new paid registration. Results post to your AWS Certification account within a few business days.

The AI Practitioner is a launch pad into AWS’s AI/ML track. The natural next step for engineers is the Machine Learning Engineer - Associate (MLA-C01), and data-focused practitioners often add the Data Engineer - Associate (DEA-C01).

Pairing the credential with hands-on work in Amazon Bedrock or SageMaker — building a RAG application or a simple model — is what turns foundational knowledge into practical skill.