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AIOps: Distributed Training

Fine tuning a GenAI model can take a significant amount of time. This course will teach you how to use the Anyscale platform, and the open source software, Ray, to better use compute resources and significantly reduce training time.

David Harris - Pluralsight course - AIOps: Distributed Training
by David Harris

What you'll learn

The process of fine tuning a generative AI model can take a lot of compute power, depending on the amount of data used in the fine tuning process, and this can cause the process to take a significant amount of time. In this course, AIOps: Distributed Training, you’ll learn to use Anyscale and Ray to manage compute resources and distribute training over multiple nodes. First, you’ll explore Anyscale. Next, you’ll discover how to use parallelism to significantly reduce fine tuning time. Finally, you’ll learn how to fine tune a GenAI model, using Anyscale. When you’re finished with this course, you’ll have the skills and knowledge of distributed training needed to fine tune a model quickly.

Table of contents

About the author

David Harris - Pluralsight course - AIOps: Distributed Training
David Harris

David loves learning!! Indeed, his hobby is reading technical documentation. He also loves helping others learn!! Dave comes to Pluralsight with a wealth of knowledge in computer science, big data, generative AI, math, statistics, video production, and, if anyone is interested, he also can help people know how to farm pigs. He will learn about anything that interests him and will teach whoever will listen. He makes his home in the desert of southwest Utah because he doesn't like snow. He also likes Vegas, which is only 1.5 hours away, so that helps, too.

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