Build a copilot app in a day with Azure OpenAI

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DURATION: 2 Day (16 hours).
Note: To complete the hands-on labs in this course, students require an Azure subscription that has been approved for access to the Azure OpenAI service. Azure OpenAI:
https://learn.microsoft.com/legal/cognitive-services/openai/limited-access

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Pre-requisites:

• Familiarity with Azure and the Azure portal.
• Experience programming with C# or Python.
• Python Check: https://learn.microsoft.com/en- us/training/paths/beginner-python/.
• C# Check: https://learn.microsoft.com/en-us/training/paths/get-started-c-sharp-part-1/.

Module 01: Introduction to Azure OpenAI

• Azure OpenAI’s language, code, and image capabilities.
• Azure OpenAI’s responsible AI practices and limited access policies.
• Types of Azure OpenAI’s base model and its deployment.
• Lab: Creation of Azure OpenAI resource/OpenAI & accessing Playground.

 
Module 02: Chat Copilot using Azure OpenAI Studio

• Brief of Azure Storage Account, Azure Cognitive Search, App Services & App Service Plans.
• Basic workflow for Copilot Creation.
• Lab: Build your own Chat Copilot using various Azure Services (Azure Portal).

 
Module 03: Art of Effective Prompting Techniques

• Understanding Text Prompting.
• Iterative Techniques for Text Prompting.
• Using Summarization Techniques.
• Inference Techniques in Text Prompting.
• Transformation Techniques for Text.
• Exercise/Documentation: Effective Prompting Techniques (Jupiter notebook).

 
Module 04: Prompt Flow Design using Azure Machine Learning Studio

• Introduction to Azure Machine Learning Studio.

Introduction to prompt flow.

Lab: Prompt flow design and implementation.

 
Module 05: Introduction to Semantic Kernel

• Introduction to Semantic Kernel.
• Working and Components of Semantic Kernel.
• Concept of Chat Plugin & its Integration into Applications.
• Integrating Semantic Kernel with Azure OpenAI models.
• Introduction to Autogen in Semantic Kernel.
• Native Functions.
• Chaining Functions using Azure OpenAI.
• Lab: Basic Labs on Semantic Functions.
• Lab: Adding skillsets to Semantic Kernel.
• Lab: Adding memories to Semantic Kernel.
• Lab: Using connectors in Semantic Kernel.
• Lab: Chaining concept in Semantic Kernel.
• Lab: Integrating Bing with Azure OpenAI using Semantic Kernel.