AI Agents are transforming the way we work. From automating complex workflows and processing documents to performing research and taking real-world actions - agents are no longer a research concept. They are being deployed in businesses today, and the demand for people who understand how to build them is growing faster than the talent available. This course gives you a complete, beginner-friendly path from understanding how Large Language Models work all the way to building your own AI agents from scratch - with no prior AI experience required.

Note: This course was created with the assistance of AI tools and platforms, including n8n, Gemini, OpenAI, and AWS Bedrock.

What is in this course?

This course is designed for anyone who wants to genuinely understand AI Agents - not just use them, but know how they work and be able to build them. Starting from the foundations of Large Language Models, you will progressively learn prompt engineering techniques, agent architecture, and hands-on agent building using n8n.

Every concept is explained in plain language with real-world analogies, and every section builds directly on the last. By the end of this course, you will have built a working Weather Agent and a RAG-based knowledge system - from a blank canvas.

Course Structure

• Concepts

• Hands-on Demonstrations

• End-to-End Agent Builds

Course Contents

• Course Introduction and Tool Setup

• What are Large Language Models

• Understanding GPT and the Transformer Architecture

• Tokens and Tokenization

• Key Parameters — Temperature, Top-k and Top-p

• Embeddings and Vector Representations

• Prompt Anatomy — The Three Layers of a Prompt

• Zero-Shot Prompting

• Few-Shot Prompting

• Chain of Thought Prompting

• ReAct Prompting — The Bridge to Agents

• Role-Based Prompting

• Structured Output Prompting

• What is an AI Agent

• Agent Components — LLM, Memory and Tools

• Multi-Agent Patterns

• Agent Frameworks — No-Code, Low-Code and Code

• End-to-End Demo — Weather Agent using n8n

• End-to-End Demo — RAG-Based Knowledge System

Special Note

This course is built around clarity and hands-on learning. Every technical concept is paired with a simple analogy so it sticks, and every prompting technique comes with a live demonstration so you see it working in real time. The two end-to-end builds at the end of the course are designed to bring together everything you have learned — so you leave with working agents, not just notes.