Google's Professional ML Engineer exam guide was rewritten in 2026: Vertex AI is renamed Gemini Enterprise Agent Platform throughout, so older study material no longer matches the product names in the questions. This guide uses the official six-section weighting as its skeleton, listing what each section tests, which official materials cover it, and what to build — plus a study schedule whose reasoning is spelled out. Official specs: $200, two hours, 50–60 multiple-choice and multiple-select questions, two-year validity, 3+ years of industry experience recommended including 1+ year on Google Cloud.
Every AI certification an engineer can register for in 2026, listed one by one: AWS AIP-C01 / MLA-C01 / AIF-C01, Google PMLE, Microsoft AI-103 and AI-500, all twelve NVIDIA exams, Databricks, Snowflake, Oracle's Agentic AI track, IBM watsonx, Salesforce Agentforce, GitHub GH-300, Anthropic's four Claude exams, Taiwan's iPAS AI Application Planner, plus the governance and audit line (IAPP AIGP, ISACA AAISM / AAIA, CertNexus CAIP) — prices, validity, and registration gates all checked against vendor pages. Two things that hit your wallet: Google's PMLE exam guide has renamed Vertex AI to Gemini Enterprise Agent Platform throughout, making pre-mid-2026 study material worthless, and the iPAS intermediate certificate is valid 5 years, not permanently.
Deploying OpenClaw to the cloud comes down to four decisions: where the Gateway binds, where state lives, who can reach it, and how you recover. Which platform you pick is the least important of them.