This course provides a comprehensive guide to deploying, managing, and optimizing AI and high-performance computing (HPC) workloads on Google Cloud. Through a series of lessons and practical demonstrations, you’ll explore diverse deployment strategies, ranging from highly customizable environments using Google Compute Engine (GCE) to managed solutions like Google Kubernetes Engine (GKE). Specifically, you’ll learn how to create clusters and deploy GKE for inference.
AI Infrastructure: Deployment Types
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您将学到什么
Describe the process of creating a GPU-accelerated cluster.
Identify how to provision a GPU-accelerated cluster on GCE.
Identify how to provision a GPU-accelerated cluster on GKE.
Identify how to deploy AI inference workloads on GKE.
您将获得的技能
- Cloud Engineering
- Distributed Computing
- Google Cloud Platform
- Containerization
- Infrastructure As A Service (IaaS)
- Application Deployment
- AI Orchestration
- Model Deployment
- Performance Tuning
- Network Planning And Design
- System Configuration
- Cloud Deployment
- Cloud Infrastructure
- Kubernetes
- Network Performance Management
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最近已更新！
December 2025
作业
4 项作业
授课语言：英语（English）
了解顶级公司的员工如何掌握热门技能
该课程共有6个模块
This module offers an overview of the course and outlines the learning objectives.
涵盖的内容
1个插件
This module details the AI Hypercomputer cluster creation process. It covers the key decisions required, including choosing a machine type, consumption option, deployment option, orchestrator, and cluster image.
涵盖的内容
1个作业6个插件
This module identifies key configuration options and optimization techniques for deploying an AI Hypercomputer cluster on Google Compute Engine (GCE). It covers selecting machine types, accelerator OS images, deployment options, and strategies for optimizing network performance.
涵盖的内容
1个作业4个插件
This module identifies configuration options for deploying an AI Hypercomputer cluster on Google Kubernetes Engine (GKE). It covers containerization, GKE modes of operation, networking configurations, and workload optimization techniques like distributed training and GPU sharing.
涵盖的内容
1个作业4个插件
This module examines optimization techniques for architecting an inference workload on GKE. It covers the GKE inference workflow, key infrastructure and model-level optimizations.
涵盖的内容
1个作业4个插件
Student PDF links to all modules
涵盖的内容
1篇阅读材料
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常见问题
Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.
更多问题
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