Azure OpenAI for Developers

Learn how to integrate OpenAI functionalities and tools in this comprehensive 3-day course

Register for the Vitual Live Session:
September 16th - $1799

Course Description

This course offers a comprehensive introduction to AI development with a primary focus on integrating OpenAI functionalities and tools. Designed for developers already familiar with foundational web technologies, this curriculum dives deep into leveraging OpenAI’s capabilities to build AI-powered applications.

Key Highlights:

Foundation: Begin with an understanding of OpenAI’s key features, capabilities, and potential applications.
Setting Up: Equip yourself with the required tools and software, including Visual Studio Code, Python, .NET, Git, Postman, NodeJS, and Microsoft C++ Build Tools. Special attention is given to troubleshooting common setup challenges.
Hands-on Challenges: Transition from theory to practice with seven extensive challenges. These span from provisioning Azure OpenAI resources, understanding API keys and endpoints, integrating various SDKs, building applications using ReactJS and ASP.NET Core, and finally, managing container deployments using Azure services.
Azure Integration: Learn the intricacies of Azure Container Registry, Azure App Service, and Azure DevOps. Delve deep into the build and release pipelines, ensuring a smooth CI/CD process.

By the end of this course, participants will be adept at creating, testing, and deploying AI-enhanced applications, with a thorough grasp of both OpenAI tools and Azure’s deployment mechanisms.

About this Course

Course Outline

Module 1: Introduction to OpenAI and Large Language Models

Provisioning Azure OpenAI Resources
Creating an Azure OpenAI resource
Create deployment models
Embeddings
Chat
ChatCompletion
Test the models in the Playground
Model Settings and Prompt Engineering
Temperature, Max Tokens, Engine, Stop Sequence
Prompt Structure:
System, User and AI Prompts
Understanding API keys and endpoints
Using the API in in Postman & cURL

Module 2: Understanding Large Language Models

What are large language models (e.g., GPT-3) and their applications?
Hands-on exploration of GPT-3’s capabilities
Building with Large Language Models

Module 3: Introduction into Azure OpenAI SDK’s

Azure OpenAI SDKs provide streamlined access to OpenAI’s AI models in Azure.
Support for popular programming languages, making it accessible to a wide range of developers.
Examples like JavaScript embedded demo show how to embed AI features in web applications.
Comprehensive tools and demos available for .NET (C#) developers, similar to Python support.
Module 4: Using the JavaScript SDK with ReactJS

Module 4: Building a ReactJS application with Azure OpenAI

Integration of Azure OpenAI JavaScript SDK is essential for interaction with OpenAI models.
Design a user-friendly interface and use React’s component-based architecture for user interactions with AI.

Module 5: Azure Integration and Advanced Topics

Integrating OpenAI into Azure
Overview of Azure’s AI and machine learning services
How to use Azure Functions and Logic Apps for OpenAI integration

Module 6: Advanced OpenAI Concepts

Building Advanced OpenAI Applications

Module 7: Deployment, Best Practices, and Use Cases

Module 8: Deployment Strategies

Choosing the right deployment methods for your OpenAI applications (e.g., Containers, Functions, VMs)
Scaling and load balancing
Security, Monitoring, and Best Practices

Securing OpenAI applications on Azure
Monitoring, troubleshooting, and best practices

Module 9: Real-World Use Cases and Q&A

Explore real-world use cases of OpenAI in Azure and have a Q&A session

Challenges

Challenge 1

Provisioning Azure OpenAI Resources
Creating an Azure OpenAI resource
Create deployment models
Embeddings
Chat
ChatCompletion
Test the models in the Playground
Model Settings and Prompt Engineering
Temperature, Max Tokens, Engine, Stop Sequence
Prompt Structure:
System, User and AI Prompts
Understanding API keys and endpoints
Using the API in in Postman & cURL

Challenge 2

Introduction to Azure OpenAI SDKs
Overview of available SDKs
Javascript embedded demo
Integrating the C# SDK – demos for AI-050 have a c# and Python option
Integrating the Python SDK – demos for AI-050 have a c# and Python option

Challenge 3

Building a Simple ReactJS Application with Azure OpenAI
Setting up a ReactJS project
Integrating the Azure OpenAI JavaScript SDK
Creating user interface
Testing and debugging

Challenge 4

Building a Simple ASP.NET Core Application with Azure OpenAI
Setting up an ASP.NET Core project
Integrating the Azure OpenAI C# SDK
Developing AI-powered server-side logic
Testing and debugging
Docker image creation

Challenge 5

Create an Azure Container Registry (ACR) instance.
Create an Azure App Service instance to host container
Upload container to ACR
Deploy container to App Service

Challenge 6

Create a new project in Azure DevOps
Set up code repository
Create a new build pipeline.
Use the existing Dockerfile to define the build process.
Add tasks to build and push the Docker image to the Azure Container Registry.
Trigger the build

Challenge 7

Create a new release pipeline.
Add an artifact that points to the build pipeline’s output.
Define the deployment process.
Use the deployment center
Trigger the release
Validate deployment

Duration

3 Days

Prerequisites

Visual Studio Code
Python for Visual Code Studio
This guide walks you through installing a Python interpreter and the extension needed for using VSCode for Python development.
Note: Please use version 3.10 of Python. There are issues with existing libraries.
Upgrade pip to the latest version
If you are seeing this error “ERROR: Could not build wheels for hnswlib, which is required to install pyproject.toml-based projects” then use the following link as a fix.
.Net 6 LTS
Git installed
Postman
NodeJS 18+
Microsoft C++ Build Tools