Learning Paths for Semantic Kernel

Sophia Lagerkrans-Pandey

We are excited to highlight new learning content released focused on Semantic Kernel.

  1. APL-2005 Develop AI agents using Azure OpenAI and the Semantic Kernel SDK – Training | Microsoft Learn
  2. Student Hub Overview – Microsoft Learn Student Hub | Microsoft Learn

.NET Conf Student Zone – Explore AI

On the .NET Conf Student Zone you can learn in a beginner-friendly virtual event where you’ll learn how to build projects using C# and .NET. In the Explore AI dedicated section, shown below, you can learn about AI, how to get started, and using GPT models to improve text completions with Semantic Kernel.

Image Explore AI

Who Needs Semantic Kernel?  – Join Semantic Kernel expert, John Maeda VP of Design and Ai as he introduces Blake – the app developer who came back from December holidays in 2023 to a boss suddenly wanting AI in their App ASAP.

Semantic Kernel for BeginnersGet introduced to Semantic Kernel for developers, covering essential components such as the kernel SDK, planners, memories and connectors. Learn through examples and applications.

APL-2005 Learning Path: Developing AI Agents using Azure OpenAI and the Semantic Kernel SDK

Microsoft Learn released a new learning path called APL-2005 Develop AI agents using Azure OpenAI and the Semantic Kernel SDK – Training | Microsoft Learn. This learning path is focused on how to use the Semantic Kernel SDK to build intelligent applications that automate tasks and perform natural language processing.

Some suggested Prerequisites are:

  • Experience programming in C#.
  • Visual Studio Code IDE installed.
  • Familiarity with Azure and the Azure portal.
  • Access to Azure Open AI Services.

There are five key Modules in the Learning Path

  1. Building your KernelThis module introduces the Semantic Kernel SDK. Learn how the kernel connects code to large language models to extend functionality with generative artificial intelligence.
  2. Create Plugins for Semantic Kernel – This module explores Semantic Kernel SDK plugins. Learn how plugins to the SDK are used to accomplish customized tasks and create intelligent applications.
  3. Give your AI Agent Skills – This module explores native functions in the Semantic Kernel SDK. Learn how native functions can accomplish customized tasks, effectively giving your AI agent a “skill.”
  4. Use Intelligent Planners – This module introduces different ways to automatically invoke functions using the Semantic Kernel SDK. Learn how planners can generate plans to accomplish tasks and how to fine-tune planners to optimize performance.
  5. Guided Project – Create an AI Travel Agent – This module guides you through the steps required to develop a proof-of-concept AI Travel assistant with the Semantic Kernel SDK. By the end of this module, you complete a small chatbot application.


Please reach out if you have any questions or feedback through our Semantic Kernel GitHub Discussion Channel. We look forward to hearing from you! We would also love your support, if you’ve enjoyed using Semantic Kernel, give us a star on GitHub.

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  • Laurent Kempé 0

    Really enjoyed this learning path about Semantic Kernel 👍🏼
    I’ve got a much better understanding now of the capabilities of Semantic Kernel.
    Thanks for building it

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