• Get started with Azure OpenAI Service

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.
• Build natural language solutions with Azure OpenAI Service

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
• Apply prompt engineering with Azure OpenAI Service

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.
• Generate code with Azure OpenAI Service

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

• • Use natural language prompts to write code
  • Build unit tests and understand complex code with AI models
  • Generate comments and documentation for existing code
• Generate images with Azure OpenAI Service

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

• • Describe the capabilities of DALL-E in the Azure openAI service
  • Use the DALL-E playground in Azure OpenAI Studio
  • Use the Azure OpenAI REST interface to integrate DALL-E image generation into your apps
• Implement Retrieval Augmented Generation (RAG) with Azure OpenAI Service

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

• • Describe the capabilities of Azure OpenAI on your data
  • Configure Azure OpenAI to use your own data
  • Use Azure OpenAI API to generate responses based on your own data