Ready to get started with AI Hypercomputers? This course makes it easy! We'll cover the basics of what they are and how they help AI with AI workloads. You'll learn about the different components inside a hypercomputer, like GPUs, TPUs, and CPUs, and discover how to pick the right deployment approach for your needs.
AI Infrastructure: Introduction to AI Hypercomputer
Gain insight into a topic and learn the fundamentals.
Intermediate level
Some related experience required
2 hours to complete
Flexible schedule
Learn at your own pace
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
Details to know
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Recently updated!
August 2025
Assessments
1 assignment
Taught in English
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There are 2 modules in this course
In this course, you'll gain a deeper understanding of how to effectively utilize Google Cloud GPUs for accelerating AI training and inference, including selecting appropriate options and optimizing performance.
What's included
1 assignment7 plugins
Student PDF links to all modules
What's included
1 reading
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Frequently asked questions
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.
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