Учасник із 2025
Introduction to AI and Machine Learning on Google Cloud
Earned лип. 20, 2026 EDT
Build a Certification Study Guide: PMLE
Earned трав. 3, 2026 EDT
Іспит "Сертифікований викладач Google рівня 1" (A)
Earned трав. 2, 2026 EDT
Deploy Your First Agent
Earned квіт. 29, 2026 EDT
Build and Deploy Agents in Production
Earned квіт. 29, 2026 EDT
This course introduces Google Cloud's AI and machine learning (ML) capabilities, with a focus on developing both generative and predictive AI projects. It explores the various technologies, products, and tools available throughout the data-to-AI lifecycle, empowering data scientists, AI developers, and ML engineers to enhance their expertise through interactive exercises.
Learn how to use Gemini Notebook to create a personalized study guide for the Professional Machine Learning Engineer (PMLE) certification exam. You'll review Gemini Notebook features, create a notebook, and use the study guide to practice for a certification exam.
Продемонструйте свої навички роботи з інструментами Google у класі! Щоб скласти іспит для отримання статусу Сертифікованого викладача Google рівня 1 (версія A), виконайте наведені нижче завдання й пройдіть тестування.
Take your agents from localhost to production. This course teaches you to deploy ADK agents to Agent Runtime and Cloud Run, with optional cross-session memory via Memory Bank. Explore other content in the Gemini Agent Ready (GEAR) program. Join the community forum for questions and discussions
Explore the architecture and deployment of multi-agent systems using Google’s Agent Development Kit (ADK) and Google Cloud’s robust infrastructure. You will learn to design hierarchical agent trees and deterministic workflow agents while identifying the ideal hosting environment—from serverless Cloud Run to high-performance GKE—to ensure your AI agents are secure, scalable, and production-ready. Explore other content in the Gemini Agent Ready (GEAR) program.