AWS Certified AI Practitioner Study Guide (AIF-C01)
Comprehensive curriculum covering Fundamentals of AI and ML, Fundamentals of Generative AI, Applications of Foundation Models, Guidelines for Responsible AI, and Security, Compliance, and Governance for AI Solutions across 5 chapters and 15 interactive lessons.
Complete AWS AI Practitioner Curriculum
Browse all 16 interactive lessons across 4 curriculum chapters. Every lesson includes verified blueprint takeaways, common examination traps, and interactive practice checkpoints:
Fundamentals of AI and Machine Learning
Master core machine learning taxonomy, learning paradigms, overfitting/underfitting dynamics, and essential classification metrics.
Fundamentals of Generative AI
Understand transformer architecture, subword tokenization, inference parameters (temperature, top-p), prompt engineering, and vector RAG.
Applications of Foundation Models on AWS
Master Amazon Bedrock serverless APIs, Knowledge Bases, Agents, Guardrails, SageMaker JumpStart, Canvas, and Amazon Q assistants.
Guidelines for Responsible AI, Security, and Governance
Master fairness, bias mitigation, SHAP explainability, data drift monitoring, the AWS Shared Responsibility Model, and Bedrock security safeguards.
Interactive Study Tools & Resources
Reinforce what you learn in the guide with our suite of free interactive AWS AI Practitioner tools:
65-Question Mock Exam
65 scored questions simulating Pearson VUE test day with prompt engineering and Bedrock model evaluations.
Launch Practice Exam →AIF-C01 Cram Sheet
High-yield reference for Foundation Models, tokenomics, RAG pipelines, and model evaluation metrics.
View Cheat Sheet →4-Week Study Plan
Accelerated preparation schedule focusing on core generative AI concepts, security guards, and SageMaker tooling.
View Study Plan →