AWS Certified AI Practitioner: Exam Cost, Format and Who Should Take It

The AWS Certified AI Practitioner is a foundational exam from Amazon Web Services (exam code AIF-C01). It’s for people who need to understand AI, machine learning and generative AI on AWS, including non-engineers. The exam costs $100 USD, has 65 questions and runs 90 minutes. AWS lists no prerequisite, so you can start from scratch.

What Is the AWS Certified AI Practitioner?

The AWS Certified AI Practitioner is a proctored exam that proves you know the basic ideas behind AI, machine learning and generative AI, and which AWS services apply to them. AWS ranks it as its foundational AI credential. That means it sits below the Machine Learning Engineer Associate and the Generative AI Developer Professional.

It’s built for breadth. You won’t train a model in the exam room. You’ll answer questions about what a foundation model is, when a certain approach fits a business problem, how to use AI responsibly and how to keep AI workloads secure.

That makes it a good fit for a few kinds of people:

• Career changers who want a quick, low-cost first credential in AI.
• Analysts, project managers and product people who work next to AI teams.
• Cloud and IT staff who already use AWS and want to add AI.
• Students in an AI degree who want a vendor credential on their résumé.

If you want to build and deploy models, this is a starting line, not a finish line.

How Much Does the AWS AI Practitioner Exam Cost?

AWS lists the exam at $100 USD. That’s the figure on the certification page, and it’s the lowest price among the four AWS AI and machine learning exams we cover. Taxes or local pricing may change what you see at checkout, so confirm the amount when you book.

The cost is mostly your study time. You might also pay for a prep course or practice tests, which are optional. The exam guide is free from AWS.

If you want to compare vendor exam prices side by side, our AI certifications guide lines them up with university certificates, which cost far more.

What Is the Exam Format?

Here is the format AWS publishes:

• Questions: 65 total. 50 count toward your score and 15 are unscored.
• Time: 90 minutes.
• Delivery: Pearson VUE testing center or online proctored.
• Scoring: scaled from 100 to 1,000, with a minimum passing score of 700.
• Languages: AWS lists several, including English, Spanish, Japanese and Simplified Chinese. The Italian and German versions retire after October 15, 2026.

The unscored questions are AWS testing future items. You won’t know which ones they are, so treat all 65 the same way.

A scaled score isn’t a percentage. Don’t assume 700 means 70% correct. Aim to know the material well enough that you don’t need to calculate.

What Does the Exam Cover?

AWS splits the exam into five domains, each weighted by its share of scored content.

• Fundamentals of AI and ML: 20%
• Fundamentals of Generative AI: 24%
• Applications of Foundation Models: 28%
• Guidelines for Responsible AI: 14%
• Security, Compliance, and Governance for AI Solutions: 14%

Notice where the weight sits. Generative AI and foundation models together make up more than half the scored content. If you only have time to study well in two areas, those are the two.

The AI and ML fundamentals domain covers the vocabulary: supervised and unsupervised learning, training and inference, and how a model gets evaluated. The responsible AI and security domains are smaller, but they trip up people who skip them. They’re also the most useful ones if you work in a regulated field.

What Do You Need Before You Start?

AWS lists no prerequisite. It recommends that you’re familiar with core AWS services, namely Amazon EC2, Amazon S3, AWS Lambda and Amazon SageMaker, along with IAM, the shared responsibility model, AWS Regions and pricing models.

If those names mean nothing to you, don’t worry. Plan an extra week or two to learn them. You don’t need to run them, but you should know what each one does and when you’d pick it.

You also don’t need a degree. AWS lists none, and no coding background is required.

How Do You Prepare?

Preparation is easier when you work from the exam guide rather than from a random course outline. The guide lists the tasks under each domain. Use it as a checklist.

A plan that works for most beginners:

1. Read the exam guide once, start to finish. Mark each task you can’t explain.
2. Learn the AWS basics. Know what EC2, S3, Lambda and SageMaker do, and what IAM and the shared responsibility model mean.
3. Study the heavy domains first. Applications of Foundation Models and Fundamentals of Generative AI carry 52% of the scored content between them.
4. Use the AWS console. Even 30 minutes poking at a service makes the name stick.
5. Take practice questions. They show you how AWS words things, which matters on a scenario exam.
6. Book the exam while the material is fresh. A date on the calendar keeps you moving.

Most people don’t need months. If you already know some cloud or AI vocabulary, a few focused weeks can be enough. If you’re starting cold, give yourself longer and don’t rush the date.

How Does the AWS AI Practitioner Relate to an AI Degree?

They’re different things, and one doesn’t replace the other.

An AI degree teaches you the math, programming and modeling that sit under the tools. It takes years and carries college credit. The AWS exam checks, in 90 minutes, that you know one cloud provider’s AI concepts and services. It doesn’t confer a degree, and it doesn’t qualify you for jobs that list a degree as a requirement.

A degree doesn’t replace the exam either. A graduate can finish a master’s without ever touching AWS. The exam shows an employer that you know this particular platform.

Where they fit together:

• During a degree. The exam is inexpensive, so it’s a practical add-on if you want cloud credentials alongside your coursework.
• Before a degree. If you’re unsure about committing, the exam is a way to test your interest at low cost.
• Instead of a degree. That works only for roles that don’t require one. Check postings before you rely on it.

Our ranking lists help if you’re also picking a program. For generative AI specifically, see online generative AI programs, and for a broader view, the best online AI degrees. If you’re switching fields, online AI degrees for career changers are sorted for that path. If your work is on the business side, look at online AI degrees for business.

If you aren’t sure how much a degree adds, read Is an AI Degree Worth It? before you spend money on either.

What Jobs Does It Help With?

No exam guarantees a job, and AWS doesn’t promise one. What it can do is back up a claim on your résumé: you know AI concepts and the AWS services around them.

It’s most useful for roles near AI work:

• Cloud and IT roles that are adding AI services to existing systems.
• Analyst and product roles that work with data science teams.
• Entry-level technical roles, where a recognized credential helps a thin résumé.

For engineering jobs, the picture is different. Look at the AI engineer and machine learning engineer pages, which cover duties and degree levels. Those jobs lean on programming and modeling skills that this exam doesn’t test. The AWS Certified Machine Learning Engineer Associate is a closer match for that work, and the Generative AI Developer Professional is closer still if you build on foundation models.

How Does It Compare With the Other AWS AI Exams?

AWS runs a ladder of AI and machine learning credentials. Here is where the AI Practitioner sits, using the figures AWS publishes.

• AWS Certified AI Practitioner: foundational, $100, 65 questions, 90 minutes. No prerequisite.
• AWS Certified Machine Learning Engineer Associate: associate level, $150 for the current exam, 65 questions, 130 minutes. AWS recommends 1 year of ML engineering experience and 1 year on AWS. Read our page on that exam for the version change underway.
• AWS Certified Generative AI Developer Professional: professional level, $300, 75 questions, 180 minutes. AWS recommends 2 or more years of production AWS or open-source experience. See the Generative AI Developer page.
• AWS Certified Machine Learning Specialty: retired on March 31, 2026. Our retirement page explains what replaced it.

The practitioner exam is the only one with no experience recommendation beyond basic AWS familiarity. The others assume you’ve already built things. That’s the real dividing line: this exam checks what you know, and the higher ones check what you’ve done.

What Mistakes Do First-Time Candidates Make?

A few patterns come up on foundational cloud exams, and they’re easy to avoid.

Studying only the AI theory. The exam is an AWS exam. You need to know which service fits which job, and that takes deliberate memorizing, not just reading about neural networks.

Skipping responsible AI and security. Those two domains are 14% each, so together they’re 28% of scored content. That’s as large as the biggest single domain. Treat them as full topics.

Counting questions instead of watching the clock. You have 90 minutes for 65 questions. Keep moving, flag the hard ones and come back.

Assuming 700 is 70%. The score is scaled, so you can’t convert it to a percentage of correct answers.

Waiting for perfect confidence. Practice questions will tell you more than another read of your notes. If you’re scoring comfortably on them, book the exam.

What Should You Do After You Pass?

Add the credential to your résumé and your professional profile with the exam name and the year. Then decide what the next step is, based on the job you want rather than the next badge on the ladder.

If you want to work with AI in a business or analyst role, you may already have what you need. Pair the credential with a project or two you can talk about. If you want to build, move toward Python, statistics and hands-on projects, and consider the associate exam once you’ve logged real experience on AWS.

If you’re weighing a degree next, start with the ranking lists above. A certification and a degree can sit on the same résumé, and the exam’s three-year clock gives you time to plan.

How Long Does It Last, and How Do You Renew?

The certification is valid for 3 years. To renew, you pass the latest version of the exam. There’s also a shortcut: earning the AWS Certified Machine Learning Engineer Associate recertifies the AI Practitioner automatically, per AWS.

That makes the order of the ladder sensible. If you plan to move up to the associate level anyway, you don’t need to sit the foundational exam again.

Is It Worth Taking?

For $100, the exam is a low-risk bet if any of these are true:

• You work in or near AWS and want to show AI fluency.
• You’re early in a move into AI and want a first credential.
• You’re in a degree program and want something extra to list.

It’s a weak choice if you want to prove engineering skill. For that, build projects and look at the associate-level exam. And if a job you want requires a degree, the exam won’t change that.

A good test: pull up three postings for the job you want. If AWS credentials appear, the exam is worth planning around. If they don’t, ask what the employer does look for.