Develop Generative AI Solutions with Azure OpenAI Service (AI-050)

Module 1: Introduction to Azure OpenAI Service

Get to know the connection between artificial intelligence (AI), Responsible AI, and text, code, and image generation. Understand how you can use Azure OpenAI to build solutions against AI models within Azure.

Learning objectives

In this module you'll learn how to:

• Describe Azure OpenAI workloads and access the Azure OpenAI Service.
• Understand generative AI models.
• Understand Azure OpenAI's language, code, and image capabilities.
• Understand Azure OpenAI's responsible AI practices and limited access policies.

Module 2: Get started with Azure OpenAI Service

This module provides engineers with the skills to begin building an Azure OpenAI Service solution.

Learning objectives

By the end of this module, you'll be able to:

• Create an Azure OpenAI Service resource and understand types of Azure OpenAI base models.
• Use the Azure OpenAI Studio, console, or REST API to deploy a base model and test it in the Studio's playgrounds.
• Generate completions to prompts and begin to manage model parameters.

Module 3: Build natural language solutions with Azure OpenAI Service

This module provides engineers with the skills to begin building apps that integrate with the Azure OpenAI Service.

Learning objectives

By the end of this module, you'll be able to:

• Integrate Azure OpenAI into your application.
• Differentiate between different endpoints available to your application.
• Generate completions to prompts using the REST API and language specific SDKs.

Module 4: Apply prompt engineering with Azure OpenAI Service

Prompt engineering in Azure OpenAI is a technique that involves designing prompts for natural language processing models. This process improves accuracy and relevancy in responses, optimizing the performance of the model.

Learning objectives

By the end of this module, you'll be able to:

• Understand the concept of prompt engineering and its role in optimizing Azure OpenAI models' performance.
• Know how to design and optimize prompts to better utilize AI models.
• Include clear instructions, request output composition, and use contextual content to improve the quality of the model's responses.