AI in C# using the Microsoft Agent Framework

Learn Chat, Tool Calling, Structured Output and RAG
⏱️ Length: 7.9 total hours
👥 79 students

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Course Overview
- This course offers a practical deep dive into integrating cutting-edge AI capabilities directly within your C# applications, specifically designed for .NET developers. Learn to transform static applications into dynamic, conversational agents by harnessing the power of Large Language Models (LLMs).
- Master the implementation of modern AI paradigms within the robust C# and .NET ecosystem, focusing on building sophisticated, interactive features. Create intuitive applications that can understand context and perform complex tasks seamlessly, enhancing user experience significantly.
- Explore the innovative concept of Tool Calling, empowering your AI agents to interact with external services, databases, or APIs. This crucial skill enables C# applications to execute real-world actions, retrieve dynamic information, and extend their functionality far beyond simple conversation.
- Achieve Structured Output, ensuring your AI agents consistently return data in predictable, machine-readable formats like JSON or XML. This is vital for seamlessly integrating LLM responses into business logic, automating workflows, and ensuring robust data handling within your C# applications.
- Uncover the power of Retrieval Augmented Generation (RAG), a revolutionary approach to ground LLMs with up-to-date, domain-specific knowledge. Learn how to connect your C# AI applications to external data sources, mitigating hallucinations and ensuring they provide accurate, contextually relevant, and verifiable information.
Requirements / Prerequisites
- Solid C# Proficiency: This course assumes a foundational to intermediate grasp of C# programming, including object-oriented principles, syntax, and prior experience in .NET development, which is essential for effective learning and practical application.
- Familiarity with .NET Ecosystem: A working knowledge of the .NET framework or .NET Core, including concepts like asynchronous programming, dependency injection, and project structuring, will greatly assist in comprehending the architectural patterns demonstrated.
- Development Environment Setup: Access to a suitable C# development environment such as Visual Studio (Community, Professional, or Enterprise edition) or VS Code with the C# Dev Kit installed. Ensure you have the latest .NET SDK installed to compile and run the project code effectively.
- Internet Connection and API Keys: A stable internet connection is vital for accessing external LLM services. Participants will need to acquire API keys for services like OpenAI or Azure OpenAI, as these are fundamental for hands-on interaction with the large language models demonstrated in the course.
Skills Covered / Tools Used
- C# AI Integration Fundamentals: Gain proficiency in integrating and managing AI functionalities directly within your C# codebase, understanding the lifecycle of AI interactions, and designing scalable AI-driven solutions using established .NET practices.
- Advanced Prompt Engineering Techniques: Learn to craft highly effective prompts that elicit precise and desired responses from LLMs, including strategies for system messages, few-shot prompting, and iterative refinement, optimizing the performance and relevance of your AI interactions.
- Implementing Conversational AI: Develop the ability to build sophisticated chat interfaces that maintain context, handle multi-turn conversations, and provide natural, engaging user experiences, making your C# applications highly interactive and user-friendly.
- Leveraging Tool Calling for External Integration: Master the implementation of tool (or function) calling, enabling your C# AI agents to dynamically invoke external APIs, web services, or custom C# functions. This empowers your agents to perform actions and retrieve real-time data efficiently.
- Ensuring Structured Output Generation & Parsing: Acquire techniques for guiding LLMs to produce data in specific formats (e.g., JSON schema), and learn how to parse and validate this structured output within your C# applications, ensuring seamless data flow and robust application logic.
- Building Retrieval Augmented Generation (RAG) Systems: Understand the architecture and implementation of RAG in C#, covering concepts like document chunking, embedding generation, vector database interaction, and intelligent retrieval strategies to enhance LLMs with external knowledge bases.
- Robust AI Application Development: Learn best practices for handling errors, timeouts, and unexpected responses from LLMs, ensuring your C# AI applications are resilient, gracefully degrade when issues arise, and provide a stable, reliable user experience.
- Tools Utilized: The course will extensively use C# and the .NET SDK within Visual Studio. You will work with various libraries for interacting with LLM APIs, primarily focusing on official OpenAI .NET client libraries or similar SDKs for Azure OpenAI, demonstrating practical application integration.
Benefits / Outcomes
- Pioneer AI-Powered C# Applications: Emerge from this course with the ability to conceptualize, design, and implement sophisticated AI features directly into your C# applications, setting yourself apart in the development landscape.
- Elevate Your Professional Portfolio: Showcase a cutting-edge skill set in AI integration, demonstrating practical projects involving advanced chat, tool calling, structured output, and RAG, significantly enhancing your professional portfolio and marketability.
- Solve Complex Problems with AI: Gain the expertise to apply powerful AI techniques to real-world business challenges, from automating customer support with intelligent chatbots to building data extraction tools and knowledge-powered search systems.
- Future-Proof Your C# Skills: Position yourself at the forefront of technological innovation by mastering the integration of generative AI within the C# ecosystem, ensuring your skills remain highly relevant and in-demand in an evolving industry.
- Contribute to the AI Revolution: Become an active participant in the rapidly expanding field of artificial intelligence, equipped with the practical knowledge to build the next generation of intelligent software solutions using your existing C# expertise.
PROS
- Highly Practical and Hands-on: The course emphasizes practical implementation, guiding learners through building real-world AI features step-by-step within the C# environment, ensuring immediate applicability of learned concepts.
- Focus on Modern, In-Demand AI Techniques: Covers essential LLM functionalities like Chat, Tool Calling, Structured Output, and RAG, which are critical for developing sophisticated and competitive AI applications today.
- Tailored for C# Developers: Specifically designed to bridge the gap between .NET development and AI, allowing C# developers to leverage their existing skill set to enter the exciting world of artificial intelligence without needing to learn a new primary language.
- Comprehensive Skill Set: Provides a holistic understanding of integrating LLMs, from basic API calls to advanced techniques for grounding models and enabling them to interact with external systems effectively.
- Efficient Learning Curve: Structured to deliver significant value and practical skills in a condensed timeframe (7.9 hours), making it accessible for busy professionals seeking to quickly upskill in AI development.
CONS
- Potential External Service Dependencies and Costs: Implementing the advanced AI features demonstrated may require access to paid API services (e.g., OpenAI, Azure OpenAI), potentially incurring additional costs beyond the course fee, and creating reliance on these external providers for full functionality.