Validates skills in building, deploying, automating and monitoring machine learning and generative AI solutions on Google Cloud.
A good Machine Learning Engineer course covers the June 2026 exam guide, including Gemini Enterprise Agent Platform and generative AI, and has you run ML on Google Cloud in labs. We compared the options on currency, labs, practice and price.
Most people should start with Google's free Machine Learning Engineer path, which covers the June 2026 exam with real labs. Add GCP Study Hub for a video course with seven practice exams, and the Coursera series for production ML and MLOps. Use the Wiley guide only as background.
| Course | Best for | Format | Price |
|---|---|---|---|
 Professional Machine Learning Engineer Certification path | Free official path | Interactive | Free |
 GCP Professional ML Engineer Certification Course | Course and practice exams | Video | $39/month |
 Preparing for Google Cloud Certification - Machine Learning Engineer Professional Certificate | Production ML and MLOps | Video | $49/month |
 Gemini Enterprise Agent Platform | ADK AI Agents | MCP | A2A | Agent Platform hands-on | Video | $20 |
 Official Google Cloud Certified Professional Machine Learning Engineer Study Guide | Background reference | Book | $54 |
Google's own learning path with 17 activities of courses, labs and skill badges, covering BigQuery ML, production ML systems, MLOps with Agent Platform, generative AI and responsible AI. It includes a study-guide course.
Great fit if you want the issuer's route with real labs and current product names
Poor fit if you need ML fundamentals taught from scratch; learn those first
146 video lessons, hands-on labs and seven practice exams with explanations, plus a randomized exam and a 2-hour, 50-question simulator. The subscription includes the site's other Google Cloud certification courses, and a pass guarantee refunds you if you finish and fail.
Great fit if you want a course and practice exams in one subscription
Poor fit if you prefer a one-time purchase; choose the Wiley guide or Google's free path
Two Google courses on Coursera, Production Machine Learning Systems and MLOps Getting Started, with labs and quizzes. They go deeper on deploying and running ML than the rest of the path.
Great fit if you already use Coursera and want Google's production ML courses
Poor fit if you want full coverage of the exam guide in one place; choose Google's path
A hands-on course with 31 hours of video across 411 lectures on Agent Platform, generative AI, agents and ML services, updated September 2026. It is a platform course rather than an exam course.
Great fit if you want hands-on time with Agent Platform and generative AI services
Poor fit if you want a course organized by the exam sections; choose Google's path or GCP Study Hub
The official study guide, 368 pages on data, feature engineering, training, deployment and MLOps with Vertex AI. It includes review questions and a Sybex online practice environment with flashcards.
Great fit if you want an in-depth reference for ML engineering on Google Cloud
Poor fit if you need the June 2026 product names and generative AI topics; choose Google's path
For most people, Google's free Machine Learning Engineer path, because it covers the June 2026 exam with real labs. GCP Study Hub adds practice exams.
Yes. Google's path is free on the Starter plan, which includes 35 credits a month for labs. The $29/month Pro plan gives unlimited labs.
The Coursera series takes about 2 months at 10 hours a week, and GCP Study Hub has 146 video lessons. Plan for about 80 hours of preparation in total.
Yes. The June 1, 2026 exam guide replaced Vertex AI names with Gemini Enterprise Agent Platform, so choose current materials.