AWS AIF-C01 Resources: Blueprints, Labs, and Official Links

March 28, 2026

AWS AIF-C01 resources for blueprint checks, labs, official links, and source review.

On this page

These resources keep you close to the current AIF-C01 scope instead of wandering into general AI reading that does not improve exam judgment. Start with the official exam guide, then use the linked service docs to close the exact gap you have: GenAI concepts, AWS service fit, responsible AI, or governance controls.

Official AWS certification pages

AWS Certified AI Practitioner (AIF-C01): https://aws.amazon.com/certification/certified-ai-practitioner/
AIF-C01 Exam Guide (PDF): https://d1.awsstatic.com/onedam/marketing-channels/website/aws/en_US/certification/approved/pdfs/docs-ai-practitioner/AWS-Certified-AI-Practitioner_Exam-Guide.pdf
AWS Skill Builder exam prep (AI Practitioner): https://skillbuilder.aws/exam-prep/ai-practitioner
Pearson VUE (exam delivery and scheduling): https://www.pearsonvue.com/aws/

Read these exam-guide sections first

Target candidate description (scope and depth)
Question types, scoring, and unscored content
In-scope and out-of-scope AWS services
Mentions of AWS services on the exam (short service-name conventions)

Which official page to open for each weak area

If you are weak on…	Open this first	Then pair it with…
overall exam scope, weighting, and candidate level	AIF-C01 Exam Guide (PDF)	exam guide, study plan
core AI or ML vocabulary, use cases, and lifecycle basics	exam guide fundamentals sections	Fundamentals of AI and ML
tokens, embeddings, GenAI service fit, and Bedrock-level choices	exam guide GenAI fundamentals sections	Fundamentals of GenAI
RAG, prompt engineering, FM customization, or evaluation	exam guide FM applications sections	Applications of Foundation Models
fairness, transparency, and human oversight	exam guide responsible-AI sections	Guidelines for Responsible AI
IAM, privacy, auditability, and AI governance controls	exam guide security/governance sections	Security, Compliance, and Governance for AI Solutions

Core AWS GenAI services (docs)

Amazon Bedrock: https://docs.aws.amazon.com/bedrock/
Bedrock Guardrails: https://docs.aws.amazon.com/bedrock/latest/userguide/guardrails.html
Bedrock Knowledge Bases: https://docs.aws.amazon.com/bedrock/latest/userguide/knowledge-base.html
Bedrock Agents: https://docs.aws.amazon.com/bedrock/latest/userguide/agents.html
Bedrock Model Evaluation: https://docs.aws.amazon.com/bedrock/latest/userguide/model-evaluation.html
Amazon SageMaker AI: https://docs.aws.amazon.com/sagemaker/
Amazon Q Business: https://aws.amazon.com/q/business/
Amazon Q Developer: https://aws.amazon.com/q/developer/
Amazon Nova: https://aws.amazon.com/ai/generative-ai/nova/

Best docs by question pattern

Question pattern	Open these docs first
model access, FM selection, managed GenAI platform fit	Amazon Bedrock, Amazon Nova
RAG, grounding, enterprise knowledge retrieval	Bedrock Knowledge Bases, Amazon Q Business
agent-like workflows and tool use	Bedrock Agents
FM evaluation and quality comparison	Bedrock Model Evaluation
classic AI service fit by modality	Textract, Comprehend, Rekognition, Transcribe, Translate, Polly, Lex
responsible-AI controls and enterprise governance	AWS Responsible AI, IAM, KMS, Macie, CloudTrail, Config, Audit Manager

Foundational AI services (use-case driven)

Amazon Textract (document OCR/extraction): https://aws.amazon.com/textract/
Amazon Comprehend (NLP): https://aws.amazon.com/comprehend/
Amazon Rekognition (image/video): https://aws.amazon.com/rekognition/
Amazon Transcribe (speech-to-text): https://aws.amazon.com/transcribe/
Amazon Translate (translation): https://aws.amazon.com/translate/
Amazon Polly (text-to-speech): https://aws.amazon.com/polly/
Amazon Lex (chatbots): https://aws.amazon.com/lex/
Amazon Kendra (enterprise search): https://aws.amazon.com/kendra/
Amazon Fraud Detector: https://aws.amazon.com/fraud-detector/
Amazon Personalize: https://aws.amazon.com/personalize/
Amazon Augmented AI (A2I): https://docs.aws.amazon.com/sagemaker/latest/dg/a2i.html

Responsible AI, security, and governance

AWS Responsible AI: https://aws.amazon.com/ai/responsible-ai/
IAM: https://docs.aws.amazon.com/iam/
AWS KMS: https://docs.aws.amazon.com/kms/
Amazon Macie: https://docs.aws.amazon.com/macie/
AWS CloudTrail: https://docs.aws.amazon.com/awscloudtrail/latest/userguide/cloudtrail-user-guide.html
AWS Config: https://docs.aws.amazon.com/config/
AWS Audit Manager: https://docs.aws.amazon.com/audit-manager/
AWS Artifact (compliance reports and agreements): https://aws.amazon.com/artifact/
AWS Trusted Advisor: https://docs.aws.amazon.com/awssupport/latest/user/trusted-advisor.html
AWS Well-Architected Framework: https://aws.amazon.com/architecture/well-architected/

How to use these resources effectively

Use the official exam guide PDF as your checklist, then use these docs to fill in gaps on:

Definitions and trade-offs (prompting vs RAG vs fine-tuning)
Service purpose (what it’s for; what it is not for)
In-scope service familiarity vs out-of-scope noise
Risk controls (privacy, guardrails, auditability)

When not to overread

Do not disappear into model-training detail that belongs more to MLA-C01 than AIF-C01.
Do not memorize every AWS AI service feature page-by-page when the real gap is concept classification.
Do not start with product pages if you still confuse prompting, RAG, fine-tuning, and traditional ML.

Pair this page with the section overview, the Cheat Sheet, and the FAQ as you study.

Revised on Sunday, May 10, 2026

FAQ

Glossary