- Course
AI-enabled Application Integration with Semantic Kernel
Learn how to use Semantic Kernel to connect language models with .NET application logic, plugins, functions, retrieval, and agent workflows to build practical AI-enabled application integrations.
- Course
AI-enabled Application Integration with Semantic Kernel
Learn how to use Semantic Kernel to connect language models with .NET application logic, plugins, functions, retrieval, and agent workflows to build practical AI-enabled application integrations.
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This course is included in the libraries shown below:
- AI
What you'll learn
Semantic Kernel gives .NET developers a practical way to connect language models with application logic, external services and tool. In this course, AI-enabled Application Integration with Semantic Kernel, you’ll learn how to use Semantic Kernel as the integration layer for building AI-enabled application workflows. First, you’ll see how Semantic Kernel connects application code, AI services, prompts, and plugins. You’ll create a kernel, connect it to a language model, and implement a prompt-based function for a real application task. Next, you’ll extend the application with native functions and plugins so the model can call business logic and application services instead of relying only on what it already knows. Then, you’ll add contextual awareness using retrieval and memory patterns, so responses can be grounded in relevant application knowledge. Finally, you’ll bring prompts, plugins, functions, retrieval, and agent collaboration together in an end-to-end AI-enabled workflow. When you’re finished with this course, you’ll understand how to use Semantic Kernel to build practical AI-enabled .NET applications that connect language models.