AI Agents with .NET & Semantic Kernel - 3-Day Intensive Course
Develop modern AI agents with Semantic Kernel, .NET, and RAG tailored to enterprise needs.
In the hands-on intensive course “AI Agents with .NET & Semantic Kernel,” your team will be guided through the creation of intelligent, enterprise-specific AI agents from scratch. Over three days, you will work through all relevant concepts and technologies to realize robust, customizable agents using Microsoft Semantic Kernel, .NET, and Retrieval-Augmented Generation (RAG) that store, link, and apply knowledge in production processes.
Highlights
- Intensive 3-day course: Hands-on training with a focus on practical implementation.
- Tailored content: Customized to your team’s objectives and technical level.
- Expert guidance: Learn from experienced trainers with real-world expertise.
- Comprehensive resources: Receive detailed code templates, sample data, and step-by-step guides.
Our Shared Goal
By the end of the intensive course, your team will have developed a fully functional AI agent based on your own data-from architecture and RAG integration to secure deployment in the Azure environment. You will have deep expertise in vector search, semantic memory, prompt chaining, and tool composition and will be prepared to integrate AI agents sustainably into your business processes. You will also receive detailed code templates and sample data, hands-on projects with step-by-step guides, and an individualized roadmap with recommendations for advancing your AI strategy.
Workshop Contents
Day 1: Fundamentals & Architecture
Overview of agentic AI, LLM concepts, and RAG principles. Introduction to Microsoft Semantic Kernel: architecture, KernelFunctions, Planner, Memory, and tools. Setting up an agent project with .NET, Azure OpenAI, and Qdrant. Developing initial tool classes. Mini use case: conversational agent with basic capabilities.
Day 2: Data Integration & Storage
Creating and storing embeddings (text to vector) and integrating Qdrant as a vector store. Building a semantic memory for agent knowledge. Retrieval and prompt context enrichment (live RAG). Implementing tool compositions and dynamic query flows with function calling and Planner.
Day 3: Agent Orchestration & Deployment
Agents with complex behavior: Planner, tool selection, and dynamic workflows. Building an interactive interface (e.g., Blazor or Web API). Combining tool functions for data retrieval, decision logic, and response generation. Security, governance, and scaling in the Azure environment. Final demo: your team presents its own agent prototype.
We'd love the opportunity to work together.
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