If you are planning to take the AWS Certified AI Practitioner (AIF-C01) certification, the first step is to understand the exam itself.

Before starting preparation, you should know:

• What is the exam format?

• How many questions are there?

• How much time do you get?

• What topics are covered?

• What types of questions can appear?

• How is the exam conducted?

This article covers the basic exam structure and syllabus so you can build your preparation plan around the actual exam requirements.

1. What is AWS Certified AI Practitioner?

The AWS Certified AI Practitioner is a foundational-level AWS certification focused on Artificial Intelligence (AI), Machine Learning (ML), and Generative AI.

The certification is designed for people who understand AI/ML concepts and how they are used on AWS, but who do not necessarily build AI/ML solutions themselves.

AWS lists the exam as AIF-C01.

2. AWS AI Practitioner Exam Format

Here is the basic exam structure:

The exam contains 65 questions in total. According to AWS, 50 questions are scored and 15 are unscored. The unscored questions are not identified during the exam.

Time available per question

90 minutes ÷ 65 questions = approximately 1 minute 23 seconds per question.

This does not mean you need to spend exactly 83 seconds on every question.

A better strategy is:

Easy question → Answer quickly

Difficult question → Flag and continue

End of exam → Return to flagged questions

AWS's exam interface allows candidates to move between questions and flag questions for later review.

3. What Types of Questions Are Asked?

The AWS AI Practitioner exam can include different question formats.

The exam can include the following question types:

• Multiple choice

• Multiple response

• Ordering

• Matching

These question types are mixed throughout the exam.

Multiple Choice

You select the one best answer from the available options.

Example:

Which AWS service is designed to provide access to foundation models for generative AI applications?

You need to identify the service that best satisfies the requirements described in the question.

Multiple Response

You may need to select more than one correct answer.

The important thing here is to carefully read whether the question asks for:

"Which TWO..."

or

"Which THREE..."

Do not select answers simply because they appear technically correct. Choose the answers that satisfy the specific requirements in the question.

Ordering Questions

You may be asked to arrange steps in the correct sequence.

For example:

Arrange the steps required to build and deploy an AI application.

The exam can test whether you understand the process, rather than simply remembering definitions.

Matching Questions

You may need to match:

AWS Service → Appropriate Use Case

For example:

Questions may be more scenario-based than this simple example.

4. AWS AI Practitioner Syllabus

The exam focuses on five major domains.

Domain 1: Fundamentals of AI and ML

This domain covers the basic concepts behind Artificial Intelligence and Machine Learning.

Important topics include:

• AI concepts and terminology

• Machine Learning

• Supervised learning

• Unsupervised learning

• Reinforcement learning

• ML use cases

• Machine Learning lifecycle

• Data preparation

• Model training

• Model evaluation

• Model deployment

• Basic ML concepts

You should understand when and why AI/ML is used, not just memorize definitions.

Domain 2: Fundamentals of Generative AI

This is one of the most important areas of the exam.

Topics include:

• Generative AI fundamentals

• Large Language Models (LLMs)

• Foundation models

• Generative AI use cases

• Capabilities of Generative AI

• Limitations of Generative AI

• AWS technologies used for Generative AI

• Generative AI application architecture

You should understand questions such as:

When should Generative AI be used?

What are the limitations of an LLM?

What is a foundation model?

What is the difference between traditional ML and Generative AI?

Domain 3: Applications of Foundation Models

This domain focuses on how foundation models are used to build AI applications.

Important topics include:

• Foundation model selection

• Prompt engineering

• Prompt techniques

• Model customization

• Fine-tuning

• Training

• Model evaluation

• Foundation model performance

• AWS services for foundation models

Prompt Engineering

You should understand concepts such as:

• Zero-shot prompting

• Few-shot prompting

• Clear instructions

• Context

• Prompt structure

• Role prompting

• Output formatting

You should also understand why a particular prompting technique might be appropriate for a given scenario.

Domain 4: Guidelines for Responsible AI

AI is not only about building models.

You also need to understand how AI systems should be developed and used responsibly.

Important topics include:

• Responsible AI

• Bias

• Fairness

• Transparency

• Explainability

• Privacy

• Security

• Safety

• Governance

• Human oversight

You should be able to recognize risks associated with AI systems and understand appropriate approaches to reduce those risks.

Domain 5: Security, Compliance, and Governance for AI Solutions

This domain covers topics related to securing AI systems and understanding governance and compliance requirements.

Important areas include:

• AI security

• Data security and privacy

• IAM and permissions

• Encryption

• Data protection

• Prompt injection

• Data leakage prevention

• Logging and auditing

• Governance

• Compliance

• Data lineage

• Security best practices

AWS currently assigns 14% of scored content to this domain.

Machine Learning

Learn:

• ML types

• Training

• Validation

• Testing

• Features

• Labels

• Model evaluation

• ML lifecycle

Generative AI

Focus heavily on:

• LLMs

• Foundation models

• Tokens

• Embeddings

• Transformers

• Prompt engineering

• Hallucinations

• Context

• Model limitations

AWS AI Services

You should know the purpose and use case of relevant AWS AI/ML services.

Don't try to memorize every AWS service.

Instead ask:

"What problem does this service solve?"

Responsible AI

Understand:

Bias + Fairness + Privacy + Security + Transparency + Explainability

6. How Much Time Do You Get?

You get:

90 minutes

for

65 questions.

That gives you approximately:

1 minute 23 seconds per question.

A practical strategy could be:

First Pass

Answer questions you know immediately.

Second Pass

Return to questions that require more thinking.

Final Review

Check flagged questions and make sure you have answered everything.

The exam interface provides navigation and flag-for-review functionality.

7. Is the Exam Difficult?

The AWS AI Practitioner is a foundational certification.

However, "foundational" does not mean that you can pass simply by memorizing definitions.

Many questions are scenario-based.

For example, instead of asking:

What is Generative AI?

the exam may describe a business requirement and ask:

Which approach would be most appropriate for this requirement?

Therefore, your preparation should focus on:

Concept → AWS Service → Use Case → Scenario

rather than:

Concept → Memorization

8. How I Am Going to Prepare

For my preparation, I am going to divide the journey into multiple stages.

Stage 1 — AI Fundamentals

Learn the foundations of:

• AI

• ML

• Deep Learning

• Generative AI

Stage 2 — AWS AI Services

Understand the AWS services relevant to AI/ML and their use cases.

Stage 3 — Generative AI

Study:

• LLMs

• Foundation models

• Prompt engineering

• Embeddings

• RAG

• Model customization

Stage 4 — Responsible AI

Study:

• Bias

• Fairness

• Security

• Privacy

• Governance

• Explainability

Stage 5 — Practice

Solve:

• Topic-wise questions

• Scenario-based questions

• Mock exams

• Weak-area questions

AWS also provides official practice question sets intended to help candidates understand the exam style.

9. One Important Thing About the Exam

Don't prepare only by watching courses.

For every topic, ask yourself three questions:

1. What is it?

2. Why is it used?

3. When would I use it?

For AWS services, add one more:

4. Why would I choose this AWS service over another option?

This approach will make scenario-based questions much easier to understand.

10. My AI Practitioner Preparation Series

I am starting this blog as a learning-in-public journey toward the AWS Certified AI Practitioner certification.

In the upcoming articles, I will cover the syllabus step by step.

Planned Series

Part 1: AWS AI Practitioner Exam Format & Syllabus ← You are here

Part 2: AI Fundamentals

Part 3: Machine Learning Fundamentals

Part 4: Generative AI Fundamentals

Part 5: Large Language Models

Part 6: Foundation Models

Part 7: Prompt Engineering

Part 8: Embeddings and RAG

Part 9: AWS AI/ML Services

Part 10: Responsible AI

Part 11: AI Security, Compliance & Governance

Part 12: Scenario-Based Questions

Part 13: Mock Exam #1

Part 14: Mock Exam #2

Part 15: Final Revision

Final Thoughts

The first step toward passing any certification is understanding what the exam actually tests.

For the AWS Certified AI Practitioner:

65 questions + 90 minutes + AI/ML + Generative AI + Foundation Models + Responsible AI + Security, Compliance & Governance

Once you understand the structure, you can create a much more focused preparation plan.

This is only the beginning of my AWS AI Practitioner preparation journey.

Next: AI Fundamentals — What exactly is Artificial Intelligence?