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End to End LLMs with Azure

End to End LLMs with Azure

Instructors: Noah Gift

1,718 already enrolled

Included with

Learn more

1 module

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

1 module

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Create Large Language Model endpoints in Azure
Use GitHub Actions to deploy a containerized application for LLMs

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

2 assignments

Taught in English

91%

of learners achieved a positive career outcome

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There is 1 module in this course

This comprehensive course equips you with skills to leverage Azure for building and deploying Large Language Model (LLM) applications. Learn to use Azure OpenAI Service for deploying LLMs, utilizing inference APIs, and integrating with Python. Explore architectural patterns like Retrieval-Augmented Generation (RAG) and Azure services like Azure Search for robust applications. Gain insights into streamlining deployments with GitHub Actions. Apply your knowledge by implementing RAG with Azure Search, creating GitHub Actions workflows, and deploying end-to-end LLM applications. Develop a deep understanding of Azure's ecosystem for LLM solutions, from model deployment to architectural patterns and deployment pipelines.

Module details

This week, you will explore architectural patterns and deployment of large language model applications. By studying RAG, Azure services, and GitHub Actions, you will learn how to build robust applications. You will apply your learning by implementing RAG with Azure search, creating GitHub Actions workflows, and deploying an end-to-end application.