AI Application Development for .NET: Chat, RAG, and Vector Search

Integrating generative AI into the .NET ecosystem is now more accessible than ever through modern abstraction libraries. This text-based course guides you through the process of creating sophisticated AI-driven features—from semantic search for product catalogs to context-aware customer service chatbots—using standard C# patterns and the latest industry practices. You will transition from a traditional software developer to an AI-capable engineer, learning how to leverage Large Language Models to solve complex business problems. By reading detailed written explanations and exploring practical code snippets, you will gain the skills to build applications that can reason, search, and interact naturally with users. What you'll learn: - Understand the fundamentals of LLM orchestration using the latest Extensions AI libraries (MEAI). - Configure and switch between cloud-based providers and local models like Ollama for flexible deployment. - Implement vector search and semantic retrieval using embeddings and specialized vector databases. - Build Retrieval-Augmented Generation (RAG) systems to ground AI responses in your own specific data. - Apply function calling to enable AI models to interact with your application logic and real-time data. - Practice core AI tasks such as text summarization, sentiment analysis, and structured data extraction. The course begins with foundational definitions of AI terminology and setup procedures before moving into the practical implementation of chat streaming and vector storage. You will work through written examples that demonstrate how to manage conversation context and integrate high-dimensional data into your applications. This course is designed for beginners in the AI space; a basic understanding of C# is helpful, but no prior machine learning experience is required. Start your journey into AI-powered software development today.