AWS Certified AI Practitioner (AIF-C01) Study Guide 2026: Syllabus, Exam Topics & Study Plan -Edureify
๐Ÿ“‹ 2026 Edition  ยท  Updated November 2026

AWS Certified AI Practitioner (AIF-C01) Study Guide 2026

Complete exam coverage for the AWS Certified AI Practitioner (AIF-C01): syllabus, domains, key topics, study plan and practical exam preparation strategy.

65
Questions
90 min
Duration
700
Passing score
5
Domains
95%
First-attempt pass rate
47K+
Candidates prepared
4.9โ˜…
Average rating
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Overall readiness (locked)
Fundamentals of AI and ML
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Fundamentals of Generative AI
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Applications of Foundation Models
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Guidelines for Responsible AI
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Security, Compliance, and Governance for AI Solutions
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Exam at a Glance

AWS Certified AI Practitioner (AIF-C01) Exam Overview

Key facts about the AWS Certified AI Practitioner (AIF-C01) exam structure, format and scoring.

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aws-ai-practitioner
Exam code
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65 questions
Total questions
โฑ
90 minutes
Duration
๐ŸŽฏ
700
Passing score
๐Ÿ“‹
5 domains
Exam domains
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Certification
Credential type
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Scoring method: Results are reported as a scaled score from 100 to 1,000 using a compensatory model, so only the overall score must reach the minimum; section-level feedback is informational. Unscored pretest items are not identified and do not count; unanswered questions are scored as incorrect with no penalty for guessing. AIF-C01 has 50 scored and 15 unscored questions and a minimum passing score of 700.. The exam may include unscored pilot questions - treat every question seriously.
Focus Areas

What should you study for the AWS Certified AI Practitioner (AIF-C01) exam?

Start with the domains that make up the AWS Certified AI Practitioner (AIF-C01) exam. Use the detailed syllabus below to work through the individual topics.

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Common mistake: Candidates often memorise terminology but struggle with scenario-based questions. Focus on when to use what, not just what exists.
🔐
Fundamentals of AI and ML (20%)
Core AI and ML concepts, practical use cases and the ML development lifecycle.
🏗
Fundamentals of Generative AI (24%)
Generative AI concepts, its business capabilities and limitations, and AWS infrastructure for generative AI.
⚡
Applications of Foundation Models (28%)
Designing foundation model applications, prompt engineering, fine-tuning and evaluating model performance.
💰
Guidelines for Responsible AI (14%)
Developing responsible AI systems and recognising the importance of transparent, explainable models.
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Security, Compliance, and Governance for AI Solutions (14%)
Securing AI systems and recognising governance and compliance requirements for AI on AWS.
Full Syllabus

AWS Certified AI Practitioner (AIF-C01) Exam Syllabus and Topics

The AWS Certified AI Practitioner (AIF-C01) exam is divided into 5 domains. Each domain covers specific skills and topics. Expand a domain to see the detailed syllabus.

AI Concepts and Terminology
AI, ML, deep learning, generative AI and agentic AI
Supervised, unsupervised and reinforcement learning
Batch, real-time, asynchronous and serverless inference
Labeled, unlabeled, structured and unstructured data
Bias, fairness and model fit
Practical AI Use Cases
When AI/ML is and is not appropriate
Regression, classification and clustering
Amazon Transcribe, Translate, Comprehend, Lex and Polly
Traditional ML vs. foundation models
ML Development Lifecycle
ML pipeline stages and model sources
Managed vs. self-hosted model APIs
Amazon SageMaker AI and Amazon Bedrock by lifecycle stage
MLOps: monitoring and retraining
Accuracy, precision, recall and F1 vs. business metrics
~13 questions
20 marks
20% of exam weight
Generative AI Concepts
Tokens, chunking, embeddings and vectors
Transformers, multimodal and diffusion models
Foundation model lifecycle
Token-based pricing
Agentic AI: tool use, memory, orchestration and MCP
Capabilities and Limitations
Hallucinations and nondeterminism
Interpretability and accuracy limits
Model selection by performance, cost, latency and compliance
Business value metrics such as ROI and efficiency
AWS Generative AI Services
Amazon Bedrock and Amazon SageMaker JumpStart
Amazon Bedrock AgentCore and Strands Agents
Amazon Quick and Kiro
Provisioned throughput vs. on-demand pricing
Regional availability and cost trade-offs
~16 questions
24 marks
24% of exam weight
Design Considerations and RAG
Foundation model selection criteria
Inference parameters such as temperature
Retrieval Augmented Generation with Amazon Bedrock Knowledge Bases
Vector stores: OpenSearch Service, Aurora, Neptune and RDS for PostgreSQL
Cost trade-offs of in-context learning, RAG, fine-tuning and distillation
AI agents for business tasks
Prompt Engineering
Context, instructions and negative prompts
Zero-shot, few-shot and chain-of-thought prompting
Prompt templates and Amazon Bedrock Prompt Management
Prompt injection, poisoning, hijacking and jailbreaking risks
Training and Fine-Tuning
Pre-training, fine-tuning and continued pre-training
Instruction tuning and domain adaptation
Data curation, labeling and RLHF
Model distillation
Evaluating Foundation Models
Human evaluation and benchmark datasets
Amazon Bedrock Model Evaluation
ROUGE, BLEU and BERTScore
LLM-as-a-judge
Evaluating RAG and agent workflows
~18 questions
28 marks
28% of exam weight
Responsible AI Development
Bias, fairness, inclusivity, robustness and safety
Amazon Bedrock Guardrails
Legal risks: IP infringement, biased output and hallucinations
Dataset diversity and balance
Overfitting, underfitting and subgroup analysis
Transparency and Explainability
Transparent vs. opaque models
Amazon SageMaker Model Cards
Safety, transparency and performance trade-offs
Human-centered design and user feedback
~9 questions
14 marks
14% of exam weight
Securing AI Systems
IAM, encryption and AWS PrivateLink
Amazon Macie for sensitive data
Shared responsibility model for AI
Prompt injection and data leakage threats
Data lineage and source citation
AI Governance and Compliance
AWS Config and Amazon Inspector
AWS Artifact, AWS CloudTrail and AWS Trusted Advisor
Data residency, retention and logging
Generative AI Security Scoping Matrix
Governance policies and review cadence
~9 questions
14 marks
14% of exam weight
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Study Plan

AWS Certified AI Practitioner (AIF-C01) Structured Study Roadmap

Choose a preparation timeline based on how much time you have available. For a plan based on your actual readiness and weak domains, use the personalised Edureify study experience. Get My Training Plan โ†’

Weeks 1-2
Core Services + Highest-Weighted Domain
Deep-dive into the most heavily tested domain. Spend more time here when its exam weight is significantly higher.
Official exam guideDomain 1 completeCore conceptsPractice questions
Week 3
Domain 2 - Hands-on Practice
Focus on scenario-based study and reinforce concepts through practical application where applicable.
Domain 2Scenario walkthroughsHands-on practicePractice questions
Week 4
Domain 3 - Deeper Concepts
Work through complex concepts and decision scenarios.
Domain 3Scenario drillsPractice examReview
Week 5
Remaining Domains + Weak Area Targeting
Identify your weaker domains and spend focused time closing those gaps.
Remaining domainsDiagnosticTargeted reviewStudy notes
Week 6
Full Simulations + Final Preparation
Use timed simulations to test your preparation and review the reasoning behind incorrect answers.
Full mock examsWrong-answer reviewFinal reviewExam logistics
Exam Strategy

Tips to pass AWS Certified AI Practitioner (AIF-C01) on your first attempt

Practical advice for applying what you know, managing questions and preparing for exam conditions.

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Applications of Foundation Models is the largest domain at 28%; know when to use RAG, prompt engineering, fine-tuning or distillation and their cost trade-offs.
🔍
Practise ordering and matching items: they score only when every step or pair is correct.
⏭
Learn to map business scenarios to the right AWS AI service, such as Amazon Bedrock, SageMaker AI, Comprehend, Transcribe, Translate, Lex or Polly.
📊
Responsible AI and Security, Compliance, and Governance together make up 28%; review Bedrock Guardrails, SageMaker Model Cards and the shared responsibility model.
🔁
With 65 questions in 90 minutes you have under 1.5 minutes per item, so answer every question; blanks count as wrong and there is no guessing penalty.
Recommended Resources

AWS Certified AI Practitioner (AIF-C01) Study Resources

Use a focused set of resources alongside the study guide rather than trying to study from everything available.

Official
Official Exam Guide
Start with the authoritative exam objectives and blueprint.
Practice Tests
AWS Certified AI Practitioner (AIF-C01) Practice Test
Practice questions with explanations and domain-level performance analysis.
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Mock Exam
AWS Certified AI Practitioner (AIF-C01) Mock Exam
Timed preparation under realistic exam-style conditions.
โ†’ Take free mock exam
Training
AWS Certified AI Practitioner (AIF-C01) Certification Training
Structured preparation with personalised learning support and adaptive practice.
โ†’ AWS Certified AI Practitioner (AIF-C01) certification online training
AI Tutor
AWS Certified AI Practitioner (AIF-C01) AI Tutor
Get help understanding concepts and work on weak areas with AI-powered learning support.
โ†’ Try AWS Certified AI Practitioner (AIF-C01) AI tutor
Reference
AWS Certified AI Practitioner (AIF-C01) Cheat Sheet
Quick-reference summaries for final revision.
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Diagnostic
AWS Certified AI Practitioner (AIF-C01) Readiness Test
Assess your preparation and identify weaker exam domains.
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Reviews

What candidates say after passing

FAQ

Frequently asked questions about AWS Certified AI Practitioner (AIF-C01)

Most candidates with relevant background can structure their preparation over several weeks, depending on their existing knowledge, available study time and exam difficulty. Use the study roadmap above as a starting point and use the readiness diagnostic to identify where you need more preparation.
The guide covers the exam overview, domains, detailed syllabus and topics, study roadmap, exam preparation tips and links to practice, mock, readiness, cheat-sheet, AI Tutor and training resources.
The guide is designed to organize your preparation around the exam syllabus. You should combine it with practice questions and timed simulations so that you can test both your knowledge and your ability to apply it.
Yes. Start with the exam overview and domain breakdown, then work through the detailed topics using the study roadmap. Candidates with less experience may need additional time for foundational concepts.
Take the Edureify readiness diagnostic to assess your preparation and identify the domains where you need to focus more.
Edureify AI can help explain concepts, identify weaker areas from practice performance and support a more personalised preparation process.

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