AIF-C01

AIF-C01 AWS AI Practitioner Certification Guide

What the AWS Certified AI Practitioner (AIF-C01) exam covers, its five weighted domains, who it suits, and how to prepare, with the official exam guide.

By Code Nexus team · 5 min read · Published 2026-09-25 · Updated 2026-09-25 · Reviewed by Code Nexus team

Official exam page

Not everyone who works with AI builds it. Product managers, analysts, sales engineers and cloud generalists all need to understand what AI can and cannot do, how to use it responsibly, and which tools to reach for. AWS Certified AI Practitioner (AIF-C01) is built for exactly that audience. This guide explains what the exam covers and how to prepare. Facts come from the official AWS exam guide.

What is the AIF-C01 certification?

AWS describes the exam as designed for individuals who want to demonstrate a foundational understanding of AI concepts and AWS AI tools, with a focus on practical business applications of AI. It validates that you can:

• describe AI, machine learning and generative AI concepts, methods and strategies, in general and on AWS,
• identify the appropriate use of AI/ML and generative AI to solve business problems,
• determine the right types of AI/ML technology for specific use cases, and
• use AI, ML and generative AI responsibly.

The target candidate has up to six months of exposure to AI/ML technologies on AWS. AWS recommends familiarity with core services such as Amazon EC2, Amazon S3, AWS Lambda, Amazon Bedrock and Amazon SageMaker AI, plus the shared responsibility model, IAM and service pricing.

What the exam looks like

• 65 questions: 50 scored and 15 unscored.
• Question types: multiple choice, multiple response, ordering and matching.
• Passing score: 700 on a scaled score of 100 to 1,000, with compensatory scoring.
• No guessing penalty. Unanswered questions count as incorrect.
• Time and price: the exam guide does not state them, so check when you book.

AWS is clear about what the exam does not expect: developing or coding models, data and feature engineering, hyperparameter tuning, building pipelines, statistical analysis of models, and implementing security or governance frameworks. It tests whether you understand and can choose, not whether you can build.

What AIF-C01 teaches

The exam has five content domains.

The biggest domain, applications of foundation models, is about choosing and using models in practice: what to consider when picking one, how prompting, retrieval and fine-tuning differ, and how to evaluate results. The two smaller domains at the end, responsible AI and security and governance, together carry 28%, so they are far from an afterthought.

What people underestimate

• Prompting versus retrieval versus fine-tuning. Knowing which one solves which problem is a recurring theme.
• Responsible AI. Fairness, bias and transparency come up as scenarios, not definitions.
• Ordering and matching questions. All parts must be right, so partial knowledge does not earn credit.
• Service names. You will be expected to match a need to an AWS AI service.

Who AIF-C01 is for

• Business and product roles who work with AI teams.
• Cloud generalists who have completed CLF-C02 and want to add AI.
• Aspiring AI engineers who want a conceptual map before learning to build.
• Managers and analysts who need to judge AI proposals.

The benefits

• A responsible-use foundation. Two of the five domains are about using AI safely and within the rules.
• A clear decision framework. Knowing when to prompt, retrieve or fine-tune saves money and mistakes.
• A common vocabulary for talking to engineers.
• A parallel to the Azure route. If you also take AI-901, you see the same ideas from two providers.

Is there demand for the skill?

We could not find a reliable, current, independent figure for demand for AIF-C01 specifically, so we do not quote one. What we can say is that the skills it covers, choosing and evaluating models, grounding them in your own data, and applying guardrails, match the responsibilities Microsoft lists for an Azure AI engineer in its AI-103 study guide, such as evaluating generative applications and implementing responsible AI. We have not found evidence that employers require AIF-C01 by name. Use it as structured evidence that you have learned the concepts.

How Code Nexus prepares you for AIF-C01

Three episodes cover the exam, following the fictional company as it evaluates AI prototypes built by an acquired startup on AWS.

• Episode 38, SignalNest's Model Menu covers predictive versus generative AI, the ML lifecycle and foundation models.
• Episode 39, Prompt, Retrieve or Fine-Tune? covers prompting, retrieval-augmented generation and embeddings, and when to use each.
• Episode 40, The Fairness Review covers responsible AI, fairness evaluation and governance, and is the readiness check.

The episodes use a simulated environment that names the real AWS AI services and concepts the exam uses. It is not your own AWS account, so pair it with AWS's free training and the free tier to see the real tools. Find them in the curriculum. Because the exam is broad, some topics are taught by name and reinforced with practice questions, so expect to review the official domain outlines too.

Code Nexus prepares you for the exam. AWS delivers it and issues the certification.

A study plan

1. Read the five domain pages in the official exam guide and the in-scope services list.
2. Make a decision table for prompting, retrieval and fine-tuning: cost, effort, when to use.
3. Learn the responsible AI vocabulary with an example for each term.
4. Practise ordering and matching questions, since all parts must be right.
5. Do timed practice of 65 questions.

What to do next

To build on this, move to a developer-level exam such as AI-103, which covers designing and deploying AI applications and agents. If you have not taken a cloud fundamentals exam, read the CLF-C02 guide first. The bigger picture is in the certification roadmap, and our approach to practice is in why practice beats passive study.

Ready to start? Create a free account and open Episode 38.

Code Nexus is not affiliated with Amazon Web Services. AWS Certified AI Practitioner and its badge are trademarks of Amazon Web Services, Inc. Code Nexus prepares you for the exam; Amazon Web Services issues the certification.