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AI Infrastructure: Deployment Types

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Overview

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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.

Syllabus

Course overview

What's in it for me?

Cluster creation process

Process overview
Choosing a machine type
Choosing the consumption option
Choosing the deployment options
Choosing an orchestrator
Choosing an image
Quiz

Creating a cluster with Compute Engine

Choosing a GCE machine type
Choosing a GCE deployment option
Networking for GCE instances
Reference architecture
Quiz

Building with Google Kubernetes Engine (GKE)

Containerizing an AI application
Networking for GKE cluster deployments
Optimizing an AI workload
GPU sharing strategies
Quiz

Deploying with GKE for inference

Architecting for inference on GKE
GKE inference reference architecture
Optimizing inference with GKE Inference Gateway
Congratulations and next steps
Quiz

Course resources

Course resources

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