AIF-C01 exam guide: format, domains, preparation
Who the AIF-C01 exam is for
AIF-C01 is the exam for the AWS Certified AI Practitioner certification. Its content outline covers artificial intelligence, machine learning and generative AI concepts, the AWS services built around them, responsible AI and the security and governance of AI solutions.
The task statements in the exam guide are written with verbs such as "explain", "describe", "identify", "recognize" and "choose". The objectives centre on understanding concepts, matching a use case to a technique or a service, and recognising the limits of a solution. Training and fine-tuning appear as processes to describe. It can serve anyone who needs a structured view of AI concepts and of the related AWS services, whether or not they build models.
Exam format
| Parameter | Value |
|---|---|
| Exam code | AIF-C01 |
| Duration | 90 minutes |
| Scored questions | 50 |
| Unscored questions | 15, with no effect on the score |
| Question types | Multiple choice, multiple response, ordering, matching |
| Scoring scale | 100 to 1,000 |
| Passing score | 700 |
| Exam guide version | 1.1, dated April 30, 2026 |
Question types in detail
- Multiple choice: one correct response and three incorrect responses (distractors).
- Multiple response: two or more correct responses out of five or more options; all correct responses must be selected to receive credit.
- Ordering: a list of 3–5 responses to place in the correct order to complete a task.
- Matching: a list of responses to match with a list of 3–7 prompts; all pairs must be correct to receive credit.
Ordering and matching questions give credit only when the whole answer is correct, so partial knowledge of a process is not enough.
Domains and weights
The exam guide defines five domains, each split into task statements.
| Domain | Weight | Task statements |
|---|---|---|
| Fundamentals of AI and ML | 20 % | Basic AI concepts and terminologies; practical use cases for AI; the AI/ML development lifecycle |
| Fundamentals of GenAI | 24 % | Basic concepts of generative AI; capabilities and limitations of GenAI for business problems; AWS infrastructure and technologies for building GenAI applications |
| Applications of Foundation Models | 28 % | Design considerations for applications that use foundation models; prompt engineering techniques; training and fine-tuning of foundation models; methods to evaluate foundation model performance |
| Guidelines for Responsible AI | 14 % | Development of responsible AI systems; transparent and explainable models |
| Security, Compliance, and Governance for AI Solutions | 14 % | Methods to secure AI systems; governance and compliance regulations for AI systems |
Applications of Foundation Models weighs more than any other domain. Responsible AI and security together carry the same weight as that single domain, so they deserve dedicated study time.
What changed in guide version 1.1
The exam guide is at version 1.1, dated April 30, 2026. The revision history lists the changes. Among the objectives that are new or extended:
- Agentic AI: the basic definitions now include agentic AI, and a new objective asks you to define foundational agentic AI concepts, such as multi-agent system patterns, the Model Context Protocol (MCP), memory management, tool usage and workflow orchestration.
- Inferencing types: asynchronous and serverless inferencing are now listed alongside batch and real-time.
- Token-based pricing: a new objective covers the token-based pricing model and its effect on cost and performance for inference.
- Context engineering: a new objective covers the role of context engineering in foundation model applications.
If you use study material written for an earlier version of the guide, check these topics separately, and compare the current list of in-scope services with the one in your material.
How to prepare
- Read the official certification page for registration and current exam conditions.
- Read the AIF-C01 exam guide, then each domain page. Copy every objective into a checklist.
- Build a glossary first: AI, ML, deep learning, generative AI, agentic AI, foundation model, inference, fine-tuning, prompt engineering, retrieval and evaluation metrics. Domains 2 and 3 rely on this vocabulary.
- For each AWS service named in the guide, note what problem it solves and how it differs from the closest service, for example Amazon Transcribe, Amazon Translate and Amazon Polly.
- Spend time on the version 1.1 topics listed above, since older courses and notes may not cover them.
- Give the responsible AI and security domains a dedicated session rather than leaving them to the end.
- Practise with our AIF-C01 practice exam under timed conditions, then review each missed question in the free study mode.
- Shortly before the exam, re-check the revision history in case the guide has changed again.
Practice Exam AIF-C01: AWS Certified AI Practitioner
25 free questions with explanations, no account needed.