A certification mentioned on this page has been retired. Microsoft Certified: Azure AI Engineer Associate (AI-102) is no longer available to take. Microsoft reports the retirement date as 2026-06-30. The replacement is Microsoft Certified: Azure AI Apps and Agents Developer Associate (AI-103). Read any reference below as historical, not as advice to take this retired exam. Check the successor's current requirements before planning your preparation.
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Quick answer
The AWS Certified AI Practitioner (AIF-C01) is AWS's gentlest AI exam — foundational level, no coding, and passable in roughly four to six weeks of part-time study even if you have never opened the AWS console for a living. The preparation that works is unglamorous: study the official exam guide's domains, work through AWS's own free training path, and drill practice questions until your scores sit comfortably above the passing line. This guide gives you the week-by-week plan, the resources worth your time, and the mistakes that sink first-timers.
Where we would start
The study plan above ends in practice papers, and this is the set we would use for them — four full-length AIF-C01 exams with explained answers. It teaches nothing new by design; it tells you whether the six weeks worked.
The table below compares 4 certifications on provider, level, realistic time, coding needed and best for.
| Certification | Provider | Level | Realistic time | Coding needed | Best for |
|---|---|---|---|---|---|
| AWS Certified AI Practitioner (AIF-C01) | AWS | Foundational | ~4–6 weeks of prep | No | The exam this guide prepares you for |
| Azure AI Fundamentals (AI-900) | Microsoft | Foundational | ~2–4 weeks of prep | No | The equivalent exam if your world is Microsoft |
| AWS Certified Machine Learning Engineer – Associate (MLA-C01) | AWS | Associate | ~2–3 months of prep | Yes (Python) | The technical next step after AIF-C01 |
| AWS Certified Cloud Practitioner (CLF-C02) | AWS | Foundational | ~2–4 weeks of prep | No | Optional general-AWS grounding, not a prerequisite |
Is the AWS AI Practitioner hard to pass?
No — by AWS exam standards it is the accessible one, designed for business and non-engineering roles as much as for technologists. The difficulty is not depth; it is wording. AWS exams test through scenarios ('a company wants to…, which service should it use?'), so the skill being examined is mapping situations to services and concepts, not reciting definitions. People fail AIF-C01 for two reasons: they skim the generative-AI material because it feels familiar from using chatbots, or they never practise the scenario phrasing before meeting it under time pressure. Both are fixable with the plan below.
Our full assessment of whether this credential deserves a place on your CV is in the AWS AI Practitioner review; this guide assumes you have decided to sit it and want to pass first time.
What's actually on the exam?
Study from the official exam guide, not from a course's table of contents. The published domains cover fundamentals of AI and machine learning, fundamentals of generative AI, applications of foundation models, responsible AI, and the security, compliance and governance that wraps AI workloads. Question count, duration and format are set out in the same guide.
Read the weightings carefully. The generative-AI and foundation-model domains together carry substantial weight, and they are where AWS-specific services (Bedrock and its surrounding tooling) meet general concepts — the intersection candidates prepare least for.
Who should take it — and who should skip it?
Take it if your employer or target employers run on AWS and you want a proctored, no-code AI credential that their engineers will recognise. It suits analysts, project managers, sales engineers, security staff and managers in AWS shops — the wider no-code field is mapped in our no-coding guide.
Skip it if your organisation runs Microsoft — take the equivalent exam on your own stack instead (the trade-offs are in our AIF-C01 vs AI-900 comparison — or if you are an engineer who will be building models and pipelines, in which case go directly to the associate-level exam covered in our AWS ML Engineer Associate study guide. The three-cloud landscape sits in our AWS vs Azure vs Google comparison.
Not sure this is the right one for you?
Answer a few questions about your background and what you want the certificate to do, and the picker narrows it to one recommendation — from the same vetted list this page ranks from.
Try the AI Certification Picker →The week-by-week study plan
Built for about five hours a week; compress it if you have more:
- Weeks 1–2 — foundations: read the official exam guide end to end, then work the AI/ML and generative-AI fundamentals in AWS's own training path. Keep a running list of every service name you meet and what problem it solves.
- Weeks 3–4 — services and scenarios: map each domain to its AWS services, with extra time on foundation-model applications and responsible AI. Turn your service list into scenario flashcards — 'need X, which service?' — because that is the exam's native format.
- Weeks 5–6 — practice and gaps: full-length practice exams under timed conditions, review every wrong answer back to the source material, and book the real exam once practice scores sit consistently above the passing threshold.
Which resources are actually worth using?
Fewer than the internet suggests. The official exam guide is the syllabus; AWS's own training path covers it in the examiner's vocabulary; and one reputable set of practice exams supplies the drilling. A single well-reviewed third-party video course can substitute for the official path if you prefer taught lessons — but adding a second and third course is displacement activity, not preparation. Nothing on this exam requires paid tooling; a free-tier AWS account for poking at the console helps intuition but is optional at this level.
How should you use practice exams?
As a diagnostic, not a script. Take the first practice test early — after week two — to find your weak domains while there is still time to fix them, not as a graduation ceremony at the end. Review wrong answers to the source material the same day, and track scores by domain rather than overall: a comfortable average can hide a failing domain that the real exam will find. Book the real thing when domain-level scores are consistently above the passing line, and stop drilling the same question bank once you start recognising answers — recognition inflates scores without adding knowledge.
What happens on exam day?
You sit it online proctored or at a test centre, booked through AWS's exam portal. Online proctoring demands a bare desk, a webcam sweep and an interruption-free room — factor that in if home is busy. Tactically: the exam rewards flag-and-return. Scenario questions reward a first fast pass answering everything you are sure of, then a second pass on flagged items; running the clock out on question eleven is the classic self-inflicted fail. Unscored experimental questions may be mixed in, so do not let one bizarre question rattle you.
Where most AIF-C01 advice gets it wrong
The exam-dump economy is the big one. Memorising leaked questions violates the exam agreement, risks certificate revocation, and — the practical point — produces certificate holders who cannot answer the first follow-up question at work. The credential's entire value is that it is proctored; cheating it buys a signal you then personally falsify. The subtler error is memorising service names without use-cases. Candidates who can recite the Bedrock feature list still fail scenario questions asking which tool fits a situation — and that mapping, not the vocabulary, is also the part that makes you useful in meetings afterwards.
Verdict
Treat AIF-C01 as a four-to-six-week project: official exam guide, AWS's own training path, one practice-exam set, book when domain scores clear the line. It is the right first proctored credential for anyone in an AWS-stack organisation who wants AI literacy with teeth — and if you are unsure it is the right exam at all, our 2026 rankings and honest take on whether AI certifications are worth it put it in context. Passed it? The technical continuation is the ML Engineer Associate; the broader sequencing lives in our AI certification roadmap. Still weighing options? Our free Picker matches you in two minutes.
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Frequently asked questions
How long does it take to study for the AWS AI Practitioner?
Around four to six weeks at five hours a week if you do not work in AWS day to day, and two to three weeks if you already live in the console. The variable is scenario fluency rather than concept difficulty — the concepts are foundational, but AWS asks about them in situational form, and that phrasing takes practice to read quickly.
The shape that works inside those weeks matters more than the total. Spend the first fortnight on the official exam guide and the AI, ML and generative-AI fundamentals, keeping a running list of every service name and the problem it solves. Spend the middle weeks turning that list into scenario flashcards — "need X, which service?" — because that is the exam's native format. Reserve the final fortnight for full-length timed practice regardless of your background, and book the real exam once your domain-level scores sit above the line.
What is the passing score for AIF-C01?
AWS publishes the passing score and the scoring model in the official exam guide, and that is the only figure worth working from — it is a scaled score rather than a raw percentage, AWS revises it, and the numbers circulating on forums are frequently out of date. Read it in the guide alongside the domain weightings before you plan your revision.
The more useful target is the one you set for practice tests. Aim comfortably above the published line in every domain, not just on average: a strong overall score routinely hides one failing domain, and the real exam will find it. Track results per domain, review every wrong answer back to the source material the same day, and stop drilling a question bank once you start recognising the answers — recognition inflates scores without adding knowledge, which is exactly how people walk in over-confident.
Is the AWS AI Practitioner multiple choice?
Yes — multiple-choice and multiple-response, with AWS introducing additional question types over time. No question requires writing or reading code, and there are no hands-on labs at this level. What catches people is not the format but the phrasing: most questions are scenarios ("a company wants to…, which service should it use?"), so you are being tested on mapping situations to services rather than on reciting definitions.
Two tactical points for the sitting itself. The exam rewards flag-and-return: make one fast pass answering everything you are sure of, then a second pass on what you flagged — running the clock out on question eleven is the classic self-inflicted fail. And unscored experimental questions may be mixed in, so an item that looks bizarre is not evidence you have misjudged the syllabus. Answer it and move on.
Does the AWS AI Practitioner expire?
Yes. AWS certifications carry a recertification cycle — generally three years — after which you revalidate to keep the credential current. AWS sets and occasionally revises those terms, so check the recertification policy that applies when you certify rather than assuming today's figure will still hold when yours comes due.
This is the structural difference between a vendor exam and a course certificate, and it belongs in the decision rather than in a surprise three years later. Microsoft's fundamentals exams, including AI-900, do not expire at all, and the Coursera specializations we review stay on your profile permanently once earned. A vendor credential is a recurring commitment of both money and time — entirely worth it while you work in that ecosystem and the certificate is doing a job, and quietly wasteful once you have moved on.
What should I take after AIF-C01?
It depends on which of the two reasons you took it for. If you are heading toward technical work — building models and pipelines rather than understanding them — the AWS Certified Machine Learning Engineer – Associate (MLA-C01) is the real next rung, and it is a different order of commitment: roughly two to three months of preparation, and it does require Python.
If AIF-C01 was your literacy goal, the best next step is not another exam. Spend the following month applying what it taught you to your actual job — one workflow you improve, one thing you build with the services you can now name — because a second foundational badge adds almost nothing a hiring manager can read, while a shipped example answers the question the certificate only raises. Foundational credential, real project, then a deeper exam when the work demands it: that is the order that pays.
Keeping this current. Course formats, prices, and certification exam fees change and vary by region. We review our guides regularly — this one was last updated in July 2026 — and we always recommend confirming the specifics on the provider's official page before you enrol.