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Get started with integrating AI into your .NET applications effectively using the latest LLM best practices.
The world of Artificial Intelligence and LLMs is moving at a breakneck pace, and tooling is changing so quickly that by the time you learn something, there is something new out there that you have to learn. Understanding the basics is crucial to learn how to adapt and evolve in an ever-changing field. In this course, Ed will introduce you to AI and LLMs from the very basics, so you can get started with a solid foundation on your AI journey. He will then explain the AI landscape and all the options available to you, move to prompt engineering, and cover the available AI libraries for .NET, as well as concepts like LLM Tokens, which can be very confusing. You will learn how to work with text, streaming responses, and image content types, as well as build a basic agent and use RAG with Microsoft’s brand-new Agent Framework.
Beyond the very practical projects Ed provided (which will serve as the model for my own projects), the teaching style was excellent. I am a huge fan of Ed as a Dometrainer author.
how to actually implement LLMs in an easy, and .net-ecosystem friendly way
This is the most completed course about IA in the platform. It has a lot of good (near to reality-based) examples of use case scenarios. The instructor is really good,
Yes, this course has a lot of useful things to apply in my actual job.
What I like in this course is it's a very focused approch on the Azure AI setup, packages and code for a production grade AI Assistent/ Agent to be build.
Got the Basic knoledge on prompt engineering using the same knolodge to apply for AI assistent as a system prompt to make it a focused and only give required output.
helped me learn about AI, especially with the details on the examples.
I learned about AI implementation with .net but I think the course needs to be updated regularly so that we do not need to google the outdated contents.
Love the amount of detail in each video. Great intro to AI in .NET
Structured outputs, available .NET AI libraries, prompt engineering basics, understanding LLM tokens and embeddings.