pull base content,head:MicrosoftDocs:main,into:wwlpublishsync

Author: wwlpublish

.openpublishing.redirection.json

@@ -16073,7 +16073,12 @@
     {
       "source_path_from_root": "/learn-pr/languages/python-if-elif-else/index.md",
       "redirect_url": "/training/modules/python-boolean-types"
-    }, 
+    },
+    {
+      "source_path_from_root": "/learn-pr/wwl-data-ai/fundamentals-machine-learning/9-azure-machine-learning.yml",
+      "redirect_url": "https://learn.microsoft.com/training/modules/fundamentals-machine-learning/",
+      "redirect_document_id": false
+    },
     {
       "source_path_from_root": "/learn-pr/wwl-data-ai/fundamentals-generative-ai/3-language models.yml",
       "redirect_url": "https://learn.microsoft.com/training/modules/fundamentals-generative-ai/",

learn-pr/paths/develop-ai-agents-on-azure/index.yml

@@ -28,6 +28,7 @@ modules:
 - learn.wwl.ai-agent-fundamentals
 - learn.wwl.develop-ai-agent-azure
 - learn.wwl.build-agent-with-custom-tools
+- learn.wwl.develop-ai-agent-with-semantic-kernel
 - learn.wwl.orchestrate-sk-multi-agent-solution
 trophy:
   uid: learn.wwl.develop-ai-agent-on-azure.trophy

learn-pr/wwl-data-ai/develop-ai-agent-with-semantic-kernel/1-introduction.yml

@@ -0,0 +1,13 @@
+### YamlMime:ModuleUnit
+uid: learn.wwl.develop-ai-agent-with-semantic-kernel.introduction
+title: Introduction
+metadata:
+  title: Introduction
+  description: Learn how to create Azure AI Agent Service agents with Semantic Kernel.
+  author: buzahid
+  ms.author: buzahid
+  ms.date: 03/25/2025
+  ms.topic: unit
+durationInMinutes: 2
+content: |
+  [!include[](includes/1-introduction.md)]

learn-pr/wwl-data-ai/develop-ai-agent-with-semantic-kernel/2-understand-semantic-kernel-agents.yml

@@ -0,0 +1,13 @@
+### YamlMime:ModuleUnit
+uid: learn.wwl.develop-ai-agent-with-semantic-kernel.understand-semantic-kernel-agents
+title: Understand Semantic Kernel AI agents
+metadata:
+  title: Understand Semantic Kernel AI agents
+  description: This unit explains the Semantic Kernel SDK and Agent Framework.
+  author: buzahid
+  ms.author: buzahid
+  ms.date: 03/25/2025
+  ms.topic: unit
+durationInMinutes: 6
+content: |
+  [!include[](includes/2-understand-semantic-kernel-agents.md)]

learn-pr/wwl-data-ai/develop-ai-agent-with-semantic-kernel/3-create-azure-ai-agent.yml

@@ -0,0 +1,13 @@
+### YamlMime:ModuleUnit
+uid: learn.wwl.develop-ai-agent-with-semantic-kernel.create-azure-ai-agent
+title: Create an Azure AI agent with Semantic Kernel
+metadata:
+  title: Create an Azure AI agent with Semantic Kernel
+  description: Learn how to use the Semantic Kernel Agent Framework to create an Azure AI agent
+  author: buzahid
+  ms.author: buzahid
+  ms.date: 03/25/2025
+  ms.topic: unit
+durationInMinutes: 7
+content: |
+  [!include[](includes/3-create-azure-ai-agent.md)]

learn-pr/wwl-data-ai/develop-ai-agent-with-semantic-kernel/4-add-plugins-to-agent.yml

@@ -0,0 +1,13 @@
+### YamlMime:ModuleUnit
+uid: learn.wwl.develop-ai-agent-with-semantic-kernel.add-plugins-to-agent
+title: Add plugins to Azure AI agent
+metadata:
+  title: Add plugins to Azure AI agent
+  description: Learn how to add plugins to your Azure AI agent
+  author: buzahid
+  ms.author: buzahid
+  ms.date: 03/25/2025
+  ms.topic: unit
+durationInMinutes: 5
+content: |
+  [!include[](includes/4-add-plugins-to-agent.md)]

learn-pr/wwl-data-ai/develop-ai-agent-with-semantic-kernel/5-exercise.yml

@@ -0,0 +1,13 @@
+### YamlMime:ModuleUnit
+uid: learn.wwl.develop-ai-agent-with-semantic-kernel.exercise
+title: Exercise - Develop an Azure AI agent with the Semantic Kernel SDK
+metadata:
+  title: Exercise - Develop an Azure AI agent with the Semantic Kernel SDK
+  description: Learn how to build an agent using the Semantic Kernel SDK. This unit provides an exercise to build an agent using the Semantic Kernel SDK.
+  author: buzahid
+  ms.author: buzahid
+  ms.date: 03/25/2025
+  ms.topic: unit
+durationInMinutes: 30
+content: |
+  [!include[](includes/5-exercise.md)]

learn-pr/wwl-data-ai/develop-ai-agent-with-semantic-kernel/6-knowledge-check.yml

@@ -0,0 +1,47 @@
+### YamlMime:ModuleUnit
+uid: learn.wwl.develop-ai-agent-with-semantic-kernel.knowledge-check
+title: Knowledge check
+metadata:
+  title: Knowledge check
+  description: This unit contains a knowledge check which can help learners reinforce their understanding of the material.
+  author: buzahid
+  ms.author: buzahid
+  ms.date: 03/25/2025
+  ms.topic: unit
+durationInMinutes: 3
+content: |
+quiz:
+  questions:
+  - content: "What is the main purpose of the AzureAIAgent class in Semantic Kernel?"
+    choices:  
+      - content: "To provide a low-level interface for directly managing AI models"  
+        isCorrect: false  
+        explanation: "Incorrect. The AzureAIAgent class is built on top of Azure AI Agent Service and streamlines its features rather than providing a low-level interface."  
+      - content: "To simplify the use of Azure AI Agent Service by abstracting complex operations"  
+        isCorrect: true  
+        explanation: "Correct. The AzureAIAgent class is designed to streamline the usage of Azure AI Agent Service, reducing the complexity of setting up and managing AI agents."  
+      - content: "To replace the need for prompt templates in AI workflows"  
+        isCorrect: false  
+        explanation: "Incorrect. AzureAIAgent enhances agent interactions but doesn't replace prompt templates, which are useful for defining structured AI behavior."  
+  - content: "Which component in the Agent Framework manages conversation state and stores messages?"  
+    choices:  
+      - content: "Agent threads"  
+        isCorrect: true  
+        explanation: "Correct. Agent threads store conversations and maintain conversation state across multiple interactions."  
+      - content: "Agent chat"  
+        isCorrect: false  
+        explanation: "Incorrect. Agent chat provides the structure for multi-agent interactions but doesn't store messages."  
+      - content: "AI service connectors"  
+        isCorrect: false  
+        explanation: "Incorrect. AI service connectors allow AI models to interact with external services but don't handle conversation state."  
+  - content: "Which step is necessary to enable an AzureAIAgent to use a plugin?"  
+    choices:  
+      - content: "Modify the AI model's architecture to integrate the plugin"  
+        isCorrect: false  
+        explanation: "Incorrect. Plugins work through function calling and don't require modifications to the AI model itself."  
+      - content: "Configure the plugin in Azure portal before using it in Semantic Kernel"  
+        isCorrect: false  
+        explanation: "Incorrect. Plugins are defined and added programmatically in the codebase, not configured in the Azure portal."  
+      - content: "Define a class with methods annotated using the `kernel_function` decorator"  
+        isCorrect: true  
+        explanation: "Correct. The first step in using a plugin is defining a class and annotating its methods with the `kernel_function` decorator so the AI knows how to use them."  

learn-pr/wwl-data-ai/develop-ai-agent-with-semantic-kernel/7-summary.yml

@@ -0,0 +1,13 @@
+### YamlMime:ModuleUnit
+uid: learn.wwl.develop-ai-agent-with-semantic-kernel.summary
+title: Summary
+metadata:
+  title: Summary
+  description: This unit summarizes the key concepts covered in the module, including key features and how to use Azure AI Agent Service.
+  author: buzahid
+  ms.author: buzahid
+  ms.date: 03/25/2025
+  ms.topic: unit
+durationInMinutes: 2
+content: |
+  [!include[](includes/7-summary.md)]

learn-pr/wwl-data-ai/develop-ai-agent-with-semantic-kernel/includes/1-introduction.md

@@ -0,0 +1,17 @@
+AI agents are transforming how applications interact with users and automate tasks. Unlike traditional programs, AI agents use generative AI to interpret data, make decisions, and complete tasks with minimal human intervention. These agents use large language models to streamline complex workflows, making them ideal for automating business processes. 
+
+Developers can build AI agents using different tools, including the Semantic Kernel SDK. This open-source SDK simplifies the integration of AI models into applications. The Semantic Kernel Agent Framework supports different types of agents, including `ChatCompletionAgent`, `OpenAIAssistantAgent`, and `AzureAIAgent`. This module focuses on the `AzureAIAgent`, a type of agent that streamlines the features and functionalities of Azure AI Agent Service. 
+
+Azure AI Agent Service is a fully managed service that enables developers to securely build, deploy, and scale high-quality extensible AI agents. Using the Azure AI Agent Service, developers don't need to manage the underlying compute or storage resources. Using the Semantic Kernel Agent Framework allows developers to quickly build agents on the Azure AI Agent Service, with support for natural language processing and access to built-in tools in just a few lines of code.
+
+While Azure AI Agent Service provides a powerful foundation for building AI agents, Semantic Kernel offers additional flexibility and scalability. If you've already started developing agents with Semantic Kernel, you can seamlessly integrate Azure AI Agent capabilities, such as built-in tools and project deployment, without rewriting your code. Also, if your solution requires multiple types of agents, using Semantic Kernel ensures consistency across your implementation. Finally, if you're planning to develop multi-agent solutions, Semantic Kernel's GroupChat feature allows you to orchestrate collaborative agents efficiently—a topic covered in more detail in a later module.
+
+Suppose you need to develop an AI agent that automatically formats and emails expense reports for employees. Your AI agent can extract data from submitted expense reports, format them correctly, and send them to the appropriate recipients. To do this, you can use the Semantic Kernel Agent Framework. The plugins and functions feature allows your AI agent to interact with APIs, retrieve necessary data, and complete tasks.
+
+In this module, you learn about the core features of the Semantic Kernel SDK and the Agent Framework. You also learn how to create your own AI agents and extend their capabilities with plugin functions.
+
+After completing this module, you're now able to:
+
+- Use Semantic Kernel to connect to an Azure AI Foundry project.
+- Create Azure AI Agent Service agents using the Semantic Kernel SDK.
+- Integrate plugin functions with your AI agent.