Exam Pack: Google Professional Machine Learning Engineer

Udemy MOOC / Non-credit USD 59.99
Enroll now →
Exam Pack: Google Professional Machine Learning Engineer

About this course

Are you ready to pass the Google Professional Machine Learning Engineer (PMLE) exam on your first attempt?In 2026, Google significantly updated the PMLE blueprint to include Generative AI (Gemini), Vertex AI Agent Builder, and Low-Code AI solutions. This practice exam suite is the only resource you need to master these new topics and the core MLOps principles required to become a Google Certified Professional.These exams are designed to mimic the actual difficulty, variety, and tone of the official certification. Each question is crafted to test your ability to architect, build, and productionize ML models in real-world scenarios.What You Will Master (Exam Domains):Master the 2026 Blueprint: Practice with 48 original questions updated for the latest Google Cloud Professional Machine Learning Engineer exam requirements.Architect Generative AI Solutions: Learn to implement and evaluate LLMs using Vertex AI Model Garden, Gemini, and RAG (Retrieval-Augmented Generation).Build with Low-Code Tools: Gain confidence in using Vertex AI Agent Builder and BigQuery ML for rapid AI deployment and summarizing massive datasets.Implement Production-Grade MLOps: Master automated CI/CD pipelines, model lineage tracking with Vertex ML Metadata, and orchestration via Vertex AI Pipelines.Optimize Serving & Scaling: Practice selecting the right infrastructure (GPU vs. TPU) and deployment strategies like Canary rollouts and Traffic Splitting.Monitor & Troubleshoot AI: Learn to detect and fix Feature Drift, Concept Drift, and Training-Serving Skew in real-world production environments.Apply Responsible AI Principles: Understand how to identify bias and implement explainability using the Vertex AI What-If Tool and Explainable AI (XAI).Simulate the Real Exam

What you'll learn

  • Understand the 2026 PMLE blueprint
  • Learn to architect and evaluate Generative AI solutions
  • Gain proficiency in using low-code tools for AI
  • Master production-grade MLOps practices
  • Optimize AI deployment strategies
  • Identify and troubleshoot AI performance issues
  • Apply responsible AI principles

Course objectives

  • Prepare for the Google Professional Machine Learning Engineer exam
  • Simulate the real exam experience
  • Develop skills to implement advanced AI solutions

Skills you'll gain

Related courses

Course details are provided by the platform and may change — always confirm on the provider's site. Links may be affiliate links.