Learn how to build AI-assistants and RAG systems on Directual — without writing code. This course takes you from LLM basics to building real AI features that work with your own data. Perfect for no-coders looking to create smart, reliable, and production-ready AI tools.
What you will learn
How LLMs work — and how to use them safely
You’ll learn the fundamentals of large language models, including their strengths and weaknesses. We’ll cover what a prompt is, how hallucinations happen, and what kind of tasks LLMs are ideal for — from chatbots and summarizers to creative content generators.
How to build a RAG-based assistant that answers using your data
We’ll guide you step-by-step through building a real AI-agent that fetches context from your own documents and answers based on it. You’ll learn about vector embeddings, semantic search, and how to make your assistant reliable and context-aware — all inside the Directual ecosystem.
How to go beyond the basics with advanced techniques
Explore how to control the LLM’s output using structured formats (like JSON), enable step-by-step reasoning with chain-of-thought prompts, and test for hallucinations using logprobs. Plus, you’ll see how to run open-source models like Qwen entirely on your own machine.
