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Scale and Deploy LLMs in Production Environments

LLMs are revolutionary yet challenging to deploy and manage. This course will teach you to create and customize blueprints for deploying LLMs in a scalable, cost-effective, and secure way that aligns with your enterprise goals.

Intermediate
35m
(3)

Created by Abhishek Kumar

Last Updated Mar 28, 2024

Course Thumbnail
  • Course

Scale and Deploy LLMs in Production Environments

LLMs are revolutionary yet challenging to deploy and manage. This course will teach you to create and customize blueprints for deploying LLMs in a scalable, cost-effective, and secure way that aligns with your enterprise goals.

Intermediate
35m
(3)

Created by Abhishek Kumar

Last Updated Mar 28, 2024

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This course is included in the libraries shown below:

  • AI
  • Data
What you'll learn

Despite all the promise and potential of Large Language Models (LLMs), leveraging these LLMs in a production environment is complex and challenging.

In this course, Scale and Deploy LLMs in Production Environments, you’ll gain the ability to create and customize blueprints for deploying LLMs in a scalable, cost-effective, and secure way that aligns with your enterprise goals.

First, you’ll explore different approaches to LLM deployment in production and customize the deployment blueprint based on your use case and enterprise needs.

Next, you’ll discover considerations related to monitoring and maintaining LLMs in production.

Finally, you’ll learn how to integrate LLMs into your enterprise ecosystem safely and securely.

When you’re finished with this course, you’ll have the skills and knowledge of constructing LLM deployment blueprints needed to use them in a production environment that is scalable, secure, and responsible.

Scale and Deploy LLMs in Production Environments
Intermediate
35m
(3)
Table of contents

About the author
Abhishek Kumar - Pluralsight course - Scale and Deploy LLMs in Production Environments
Abhishek Kumar
11 courses 4.4 author rating 1641 ratings

Abhishek Kumar is a data science consultant, author, and Google Developers Expert (GDE) in machine learning. He holds a master’s degree from the University of California, Berkeley, and has been featured in the "Top 40 under 40 Data Scientist" list.

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