Azure OpenAI in .NET

2h 8mIntermediate2024-02-14

Authors

Robert Eichenseer

Course details

Explore the world of Azure OpenAI through the lens of a .NET developer. Join Robert Eichenseer—a senior services engineer at Microsoft—as he provides an overview of Azure OpenAI, demonstrating how to enrich existing application functionality with AI or use it to create brand-new .NET projects. Throughout the course, Robert includes hands-on challenges and demos that lend a real-world context to each lesson.

Learning objectives
Explore the structure and functionality of Azure OpenAI.
Learn how OpenAI models can be made available on Azure.
Describe the basic functionality of an LLM.
Explore the basics of the REST interfaces and SDKs provided by Microsoft.
Integrate AI models into your applications using REST calls or the SDK.
Review how embeddings support the semantic search for information.
Discover when and how to use embeddings to execute queries.
Review three functionalities or strategies of Semantic Kernel.

Skills covered

.NETGenerative AISoftware Development ToolsNetwork AdministrationCloud PlatformsArtificial Intelligence (AI)Network and System AdministrationCloud ComputingMicrosoftSoftware DevelopmentOne-Off

Concepts

0. Introduction

01 - Modern AI projects in .NET

1. Azure Cognitive Services and Recap

02 - Introduction to Azure OpenAI
03 - Software engineering vs. machine learning
04 - OpenAI models
05 - LLM
06 - AI-infused applications
07 - Cognitive services
08 - Bicep deployment
09 - Azure OpenAI Studio
10 - Challenge - Azure Cognitive Services
11 - Solution - Azure Cognitive Services

2. Azure OpenAI for .NET Developer

12 - Integrate OpenAI models into your applications
13 - Chat completion with REST calls
14 - Chat completion with Azure OpenAI SDK
15 - Challenge - REST and SDK
16 - Solution - REST and SDK

3. Embeddings and Vector DBs

17 - Embeddings and vectors demystified
18 - Usage of embeddings
19 - Creation embeddings and calculate distance
20 - Demo - Embeddings and search
21 - Challenge
22 - Solution

4. Microsoft Semantic Kernel

23 - Semantic Kernel
24 - Semantic Kernel - Plugin
25 - Demo - Kernel plugin
26 - Semantic Kernel - Functions
27 - Executing functions
28 - Semantic Kernel - Memories
29 - Demo - Kernel memories
30 - Semantic Kernel - Planner
31 - Demo - Planner
32 - Challenge
33 - Solution

5. Good to Know

34 - Wrapping up
35 - Billing
36 - Model fine-tuning
37 - GPT on custom data
38 - Challenge
39 - Solution