AI Certification Prep Guides

Free, exam-aligned AI certification prep guides covering AWS, Google Cloud, Microsoft Azure, NVIDIA, and Snowflake generative AI certifications.

Preparing for AI certification exams shouldn't require stitching together vendor docs, outdated blogs, and guesswork. These guides were created to give engineers and architects a clear, exam-aligned path through modern AI and generative AI certifications.

Each guide is written from real-world enterprise experience and focuses on understanding—not memorization—covering architecture, operational tradeoffs, and the reasoning behind correct answers.

What's Included

• In-depth coverage of official exam objectives
• Practical implementation guidance and architecture context
• Clear explanations of AI, ML, and GenAI concepts
• Practice tests to validate readiness before exam day

Free AI Certification Prep Guides

All guides below are provided free of charge as part of TaylorMade Software's commitment to advancing high-quality AI and cloud engineering practices.

AWS

• AWS Certified AI Practitioner (AIF-C01)
  Download study guide (PDF)

Google Cloud

• Generative AI Leader (GAIL-001)
  Download study guide (PDF)
• Professional Machine Learning Engineer (GCP-PMLE)
  Download study guide (PDF)

Microsoft

• Azure AI Fundamentals (AI-900)
  Download study guide (PDF)

NVIDIA

• NVIDIA Certified Associate – AI Infrastructure & Operations (NCA-AIOA)
  Download study guide (PDF)
• NVIDIA Certified Professional – AI Infrastructure (NCP-AI-INF)
  Download study guide (PDF)
• NVIDIA Certified – AI Operations Professional (NVAIOP)
  Download study guide (PDF)

Snowflake

• Snowflake Generative AI Certification (GAI-C01)
  Download study guide (PDF)

About the Author & Technical Editor

Author - Joe Royall
Joe Royall is an AI and cloud consultant with TaylorMade Software and a seasoned instructor specializing in Linux, cloud, and container platforms. He has designed and delivered professional training covering AI/ML infrastructure, OpenShift, Kubernetes, and large-scale Linux systems for organizations that rely on open source technologies in production.

Drawing on deep experience in systems engineering, performance tuning, and automation, Joe focuses on helping teams build reliable, scalable platforms capable of supporting modern machine learning and generative AI workloads. As an instructor for Red Hat and other training providers, he is known for making complex distributed systems and AI-enabling technologies approachable for both developers and operations engineers.

Notably, the content for these guides was produced using an AI-assisted authoring system designed by Joe himself—an applied example of using generative AI to create high-quality, domain-specific technical material at scale.

Technical Editor - J.T. Taylor
J. T. Taylor is the founder and CEO of TaylorMade Software, where he leads teams building data-intensive systems and AI-powered solutions for financial, medical, and government clients, with a strong emphasis on analytics and reporting.

With a background in mathematics, electronics, and advanced software engineering—and decades of experience delivering mission-critical systems in regulated environments— Taylor provides technical editorial oversight to ensure architectural accuracy, practical relevance, and production-grade rigor across all guides.

• Joe Royall - LinkedIn: linkedin.com/in/joeroyall
• Joe Royall - Red Hat Certification Verification: View credentials

Want Help Beyond the Exam?

TaylorMade Software helps teams move beyond certification into real-world AI platform delivery—covering architecture, security, governance, and production operations across cloud and on-prem environments.