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AIGP Exam Preparation Book 2026 - Chapter 1-13

A Practical and Structured Guide for AIGP Certification Success

Srinivas Bommena

A clear, structured guide to mastering the foundations of AI governance for the AIGP exam. This book covers Chapters 1–13 with practical explanations, exam-relevant insights, and common-trap awareness to help you approach the certification with confidence.

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About

About the Book

AIGP Exam Preparation 2026 is a structured, exam-focused guide designed to help professionals confidently prepare for the AI Governance Professional (AIGP) certification.

This book covers Chapters 1 to 13 of the AIGP Body of Knowledge, focusing on the foundational concepts of AI governance, including responsible AI principles, risk management, lifecycle controls, organizational governance, and professional responsibilities.

Rather than being a theoretical textbook, this guide emphasizes:

  • Clear explanations of complex governance concepts
  • Practical interpretation of frameworks and standards
  • Exam-relevant insights aligned to how questions are framed
  • Connections between governance principles and real-world AI systems

The content is intentionally structured to help readers:

  • Build a strong conceptual foundation
  • Understand why governance controls exist, not just what they are
  • Avoid common exam traps and misunderstandings
  • Progress systematically toward certification readiness

This book is suitable for:

  • AI, data, and software professionals
  • Risk, compliance, and governance practitioners
  • Policy and audit professionals working with AI systems
  • Anyone preparing seriously for the AIGP certification

Whether you are new to AI governance or formalizing your experience for certification, this book is designed to be a practical, dependable companion throughout your AIGP preparation journey.

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About the Author

Srinivas Bommena

Srinivas is a Generative AI Practitioner and Educator specializing in the architectural design and rigorous evaluation of LLM-powered applications. With deep experience in developing multi-agent frameworks and hybrid RAG architectures, he focus on bridging the gap between experimental AI and production-ready systems.

He is the creator of popular technical practice tests on Udemy, including the AWS Certified GenAI Developer - Professional series, and have developed comprehensive frameworks for AI project estimation and compliance. His work frequently involves industry-leading evaluation tools such as RAGAS, Giskard, and Guardrails.ai.

Driven by the mission to help IT professionals navigate the "mindset shift" required for the AI era, Srinivas provides systematic, data-driven methodologies for building AI that is not only innovative but reliable and compliant with emerging standards like the EU AI Act.

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