AI– enabled Application Integration with Semantic Kernel
Free Download AI– enabled Application Integration with Semantic Kernel
Download this premium online course featuring high-quality video training, step-by-step lessons, practical demonstrations, and expert instruction. With AI– enabled Application Integration with Semantic Kernel, you'll gain practical knowledge through structured learning, hands-on examples, and real-world applications. This comprehensive eLearning resource is ideal for students, professionals, freelancers, and lifelong learners looking to develop valuable skills and stay current with modern industry practices at their own pace.
Released 8/2026
By Gill Cleeren
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 1h 20m 54s | Size: 286.5 MB
Semantic Kernel gives .NET developers a practical way to connect language models with application logic, external services and tool.
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.
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