CLOUD AI COURSES & CERTIFICATIONS
Build a learning path that fits your work.
Compare AWS, Google Cloud, and Azure AI routes. Pair platform study with governance, security, and a small project you can explain.
Start with your role, then choose the exam.
A governance practitioner needs enough technical understanding to ask useful questions. A developer needs to build and operate the system. A security engineer needs to enforce and test its boundaries. Those routes overlap, but they need not begin with the same exam.
Use these paths as suggestions, not mandatory sequences. Provider recommendations and formal prerequisites are different. Check the official guide before booking, especially when a beta or retirement notice is involved.
OFFICIAL PROVIDER LEARNING
AWS ↗
From AI literacy to generative-AI development and ML engineering.
View courses and credentials →OFFICIAL PROVIDER LEARNING
Google Cloud ↗
A business-oriented route and a deeper technical engineering route.
View courses and credentials →OFFICIAL PROVIDER LEARNING
Microsoft Azure ↗
Current AI development and cloud/AI security credentials.
View courses and credentials →Important changes for 2026
AWS Machine Learning Specialty has retired. Microsoft’s AI-900, AI-102, and AZ-500 routes have also retired. The AWS ML Engineer Associate English exam is in an updated beta transition. The provider pages below explain the current options; the details were checked on October 27, 2026.
A project worth more than a completion screenshot
Build a small document assistant using synthetic files. Explain who can access each file, how retrieval permissions work, what is logged, which failures you tested, and how you would disable the service. Keep the architecture, risk record, and evaluation results together. That gives your learning a practical thread.
Use the practical templates ↗