Google Cloud
Google Cloud AI Infrastructure Specialization
Google Cloud

Google Cloud AI Infrastructure Specialization

Build and manage the infrastructure that powers AI. Build, deploy, and manage the Infrastructure for AI workloads.

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Get in-depth knowledge of a subject
Intermediate level

Recommended experience

4 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
Intermediate level

Recommended experience

4 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Understand the core concepts of AI Hypercomputer architecture and its value.

  • Analyze the advantages and disadvantages of various deployment and provisioning options for AI infrastructure.

  • Select the optimal accelerator (GPU, TPU) for a given AI/ML workload.

  • Evaluate the performance and efficiency of AI workloads on different accelerators to maximize business value.

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Taught in English
Recently updated!

August 2025

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Specialization - 3 course series

What you'll learn

  • Define the value and architecture of the AI Hypercomputer

  • Identify common use cases for using AI Hypercomputer

  • Explain how different types of accelerators (GPUs, TPUs, CPUs) contribute to the acceleration of AI training and inference.

  • Differentiate between various deployment options and choose the options that best suits your requirements.

Skills you'll gain

Category: Cloud Infrastructure
Category: Systems Architecture
Category: Infrastructure Architecture
Category: Google Cloud Platform
Category: Artificial Intelligence
Category: Application Deployment
Category: Cloud Computing Architecture
Category: Performance Tuning
Category: Hardware Architecture
Category: Computer Architecture

What you'll learn

  • Define the value and architecture of Graphics Processing Units (GPUs)

  • Select the appropriate GPU machine type and provisioning platform to run your GPU-accelerated clusters

  • Explore various techniques for optimizing your GPU usage

Skills you'll gain

Category: Cloud Computing Architecture
Category: Computer Architecture
Category: Cloud Infrastructure
Category: Artificial Intelligence
Category: Performance Tuning
Category: Cloud Platforms
Category: Infrastructure As A Service (IaaS)
Category: Google Cloud Platform
Category: Hardware Architecture
Category: Tensorflow

What you'll learn

  • Discuss the advantages and disadvantages of using TPUs in different scenarios.

  • Choose the right TPU option to fit your specific needs

  • Implement strategies to maximize performance and efficiency when running business-related AI workloads on TPUs.

  • Explain the concept of GPU/TPU fungibility and its significance for creating flexible machine learning workflows.

Skills you'll gain

Category: Interoperability
Category: Cloud Infrastructure
Category: Cloud Computing Architecture
Category: Performance Tuning
Category: Benchmarking
Category: Business Workflow Analysis
Category: Google Cloud Platform
Category: Tensorflow
Category: Systems Architecture
Category: Performance Improvement
Category: Product Demonstration

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Instructor

Google Cloud Training
Google Cloud
1,925 Courses3,559,076 learners

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Google Cloud

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