End to End LLMs with Azure

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End to End LLMs with Azure

Instructors: Noah Gift

1,665 already enrolled

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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

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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.

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.

What's included

16 videos11 readings2 assignments1 ungraded lab

16 videos Total 67 minutes

Meet your Course Instructor: Alfredo Deza 2 minutes
Introduction 1 minute
Getting access to Azure OpenAI Service 4 minutes
Creating an Azure OpenAI Service Resource 5 minutes
Deploy an OpenAI Model 5 minutes
Using keys and endpoints 5 minutes
Creating a simple Python example 5 minutes
Reviewing usage and quotas 2 minutes
Architectural overview 3 minutes
Overview of Azure AI Search 4 minutes
Automation and deployment with GitHub 4 minutes
Setting up Azure components 4 minutes
Using RAG with Azure OpenAI 5 minutes
Application overview 7 minutes
Deployment and automation overview 4 minutes
Using GitHub Actions with Azure 8 minutes

11 readings Total 105 minutes

About this course 10 minutes
Connect with your instructor 10 minutes
Report a problem with the course 5 minutes
Key Terms 10 minutes
External lab: Use the Azure OpenAI APIs 10 minutes
External lab: Create an Azure AI Search resource 10 minutes
External Lab: Deploy an end-to-end application 10 minutes
Key Terms 10 minutes
Course Conclusion 10 minutes
Next steps 10 minutes
Share your learning experience 10 minutes

2 assignments Total 360 minutes

Knowledge check 180 minutes
Graded Quiz 180 minutes

1 ungraded lab Total 60 minutes

Build an application with an OpenAI API 60 minutes

Instructors

Noah Gift

Duke University

40 Courses 262,549 learners

Offered by

Duke University

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