AWS Certified AI Practitioner Certification is a foundational credential for professionals who want to validate knowledge of artificial intelligence, machine learning, generative AI, foundation models, responsible AI, and AWS AI services. The current AIF-C01 exam has 65 questions, lasts 90 minutes, costs $100 USD, and requires a minimum scaled score of 700 out of 1,000 to pass. It targets professionals who use or evaluate AI solutions but do not necessarily build complex machine learning systems.
The AWS Certified AI Practitioner credential validates foundational knowledge of AI, machine learning, generative AI, and practical AI applications on AWS.
Unlike advanced machine learning certifications, the AWS Artificial Intelligence Practitioner Certification does not expect candidates to develop algorithms, perform hyperparameter tuning, build ML pipelines, or conduct advanced mathematical analysis.
The intended candidate typically has up to six months of exposure to AI/ML technologies on AWS and understands how AI services can be applied to business problems. Recommended familiarity includes services such as Amazon Bedrock, Amazon SageMaker AI, Amazon EC2, Amazon S3, and AWS Lambda, along with IAM, AWS security responsibilities, and service pricing concepts.
This makes the certification relevant to:
Cloud and IT professionals
Developers beginning with AI
Business analysts
Product professionals
Technical consultants
Solutions and presales professionals
Project managers
Students and early-career professionals
Professionals working with AI-enabled products
The current exam code is AIF-C01.
AIF-C01 Exam Detail
Current Information
Certification
AWS Certified AI Practitioner
Exam Code
AIF-C01
Level
Foundational
Questions
65 total
Scored Questions
50
Unscored Questions
15
Duration
90 minutes
Exam Cost
$100 USD
Passing Score
700/1,000
Testing Options
Pearson VUE test center or online proctored
Question Formats
Multiple choice, multiple response, ordering, matching
The AWS Certified AI Practitioner AIF-C01 exam uses 50 scored questions plus 15 unscored questions. Candidates cannot identify which questions are unscored, so every question should be treated seriously.
There is no penalty for guessing, while unanswered questions are considered incorrect.
A strong AWS AI Practitioner prep strategy should follow the official domain weightings rather than allocating equal study time to every topic.
Exam Domain
Weight
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%
The largest domain is Applications of Foundation Models at 28%, followed by Fundamentals of Generative AI at 24%. Together, these account for more than half of the scored exam content.
An important 2026 update is that the current exam guide now explicitly includes concepts such as agentic AI among foundational AI terminology. This means candidates relying on older AWS AI Practitioner notes PDF files or outdated study material should verify that their resources reflect the current exam guide.
The current AWS Certified AI Practitioner exam cost is $100 USD for one exam attempt.
AWS classifies AI Practitioner as a foundational certification. Applicable taxes and local-currency pricing can vary by region.
Your total AWS AI Practitioner certification cost may include more than the exam fee:
Exam fee: $100 USD
Optional training subscription
Practice exams
Study courses
Additional learning resources
A future retake if necessary
The official AWS Skill Builder Individual subscription currently starts at $29 USD per month, although AWS also provides several free exam-preparation resources.
Candidates searching for the AWS AI Practitioner certification fee should therefore distinguish between the mandatory exam fee and optional preparation expenses.
A useful AWS Certified AI Practitioner exam prep plan should move from concepts to services and then to scenario-based questions.
Read the current AWS Certified AI Practitioner exam guide before purchasing study material.
The exam guide defines the domains, objectives, candidate expectations, and technologies that can appear on the examination.
If you search for an AWS AI Practitioner exam PDF or AWS AI Practitioner PDF, prioritize the current official exam guide rather than relying entirely on third-party PDFs that may reflect an older blueprint.
Understand the differences between:
Artificial intelligence
Machine learning
Deep learning
Neural networks
Natural language processing
Computer vision
Training and inference
Generative AI
Large language models
Foundation models
Agentic AI
The exam tests whether you can recognize the correct technology or concept for a given business scenario.
These two areas represent 52% of scored content.
Candidates should understand concepts such as:
Foundation model selection
Prompt engineering
Retrieval-augmented generation
Model evaluation
Fine-tuning concepts
Responsible AI
Generative AI use cases
Amazon Bedrock
Amazon SageMaker AI
This weighting is one of the most important factors when planning AWS AI Practitioner exam prep.
Using an AWS Certified AI Practitioner practice exam is valuable after you have completed your first round of study.
AWS currently provides a free official practice question set containing 20 exam-style questions. The questions include feedback and recommended learning resources. AWS also provides full-length official practice assessments through its broader Exam Prep Plan.
When working through AWS AI Practitioner exam questions, do not simply memorize the correct option.
For every question, ask:
What business problem is being solved?
Which AI concept applies?
Which AWS service best matches the requirement?
Why are the other options less suitable?
Does the scenario involve cost, security, responsible AI, or governance?
This method makes AWS AI Practitioner test questions useful for identifying conceptual gaps rather than becoming a memorization exercise.
Candidates researching how to pass AWS AI Practitioner exam should focus on decision-making rather than deep coding.
A practical preparation sequence is:
Review the official AIF-C01 blueprint.
Learn core AI and ML terminology.
Study generative AI and foundation models deeply.
Understand Amazon Bedrock and SageMaker AI use cases.
Learn responsible AI principles.
Review security, compliance, IAM, and governance concepts.
Complete AWS Certified AI Practitioner sample questions.
Take an AWS Certified AI Practitioner practice exam.
Review every incorrect answer before scheduling the real exam.
AWS currently offers an Exam Prep Plan containing more than 175 exam-style questions, hands-on activities, videos, flashcards, and domain-focused learning resources, although some components require a subscription.
Candidates often search for an AWS AI Practitioner notes PDF, AWS AI Practitioner certification cheat sheet, or condensed revision guide shortly before the exam.
A useful cheat sheet should summarize:
AI vs ML vs deep learning
Generative AI terminology
Foundation model concepts
Prompt engineering
RAG concepts
Amazon Bedrock use cases
SageMaker AI use cases
Responsible AI principles
Bias, fairness, and explainability
Security and compliance
IAM concepts
AWS shared responsibility
Exam domain percentages
Use notes for final revision, but do not replace full study with a short PDF.
The AWS Certified AI Practitioner for sales professionals can make sense when a sales, presales, customer-success, or account professional works with cloud and AI solutions.
The certification focuses on recognizing AI use cases and understanding how AI technologies solve business problems rather than requiring candidates to build complex models. AWS explicitly states that coding AI algorithms, building ML pipelines, and advanced model optimization are outside the target candidate's expected tasks.
That makes AIF-C01 accessible to professionals who need to discuss AI solutions with customers, technical teams, or decision-makers.
There is no single official AWS Certified AI Practitioner salary because compensation depends on the actual job role, country, experience, technical depth, and other certifications.
Earning the credential does not automatically qualify someone for an AI engineer salary.
Its stronger value is as a foundational signal for professionals working toward positions involving:
Cloud consulting
AI product support
Technical sales
Presales
Business analysis
Cloud solutions
AI governance
Product management
Entry-level AI and cloud roles
Professionals pursuing engineering-heavy AI careers will generally need deeper hands-on skills beyond a foundational Certified Artificial Intelligence Practitioner credential.
The AWS Certified AI Practitioner AIF C01 Certification is best approached as a business-and-technology AI fundamentals exam, not a programming examination.
Start with the current AIF-C01 exam guide, prioritize generative AI and foundation models because they represent the largest share of scored content, understand the major AWS AI services, and then validate your knowledge with official AWS Certified AI Practitioner sample questions and practice assessments.
If you can consistently explain why one AI service, foundation-model approach, governance control, or responsible-AI principle fits a scenario better than the alternatives, you are preparing at the level the AWS AI Practitioner exam expects.