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Fundamentals of Agentic AI using n8n
COMING SOON!

Introduction
Artificial Intelligence is rapidly evolving from simple chatbots into autonomous systems capable of planning tasks, making decisions, using external tools, and completing business processes with minimal human intervention. This course provides a practical introduction to Agentic AI, equipping participants with the foundational knowledge needed to understand how AI agents work and how to build them using n8n.

Rather than focusing solely on automation, participants will learn the principles behind modern AI agents—including reasoning, memory, tool usage, workflows, and business applications—while developing simple, functional AI agents that solve real workplace challenges.

Who is it for?

• IT Professionals
• Business Analysts
• Automation Specialists
• Process Improvement Teams
• Digital Transformation Teams
• Software Developers
• Citizen Developers
• AI Enthusiasts
• Technical Trainers
• Anyone interested in building AI-powered business automation

Learning Objectives
By the end of this training, participants will be able to:

• Explain the principles and architecture of Agentic AI.
• Differentiate AI assistants, workflows, and autonomous agents.
• Understand how Large Language Models power AI agents.
• Build simple AI-powered workflows using n8n.
• Connect AI agents with external tools and services.
• Develop practical AI assistants for common business scenarios.
• Apply responsible AI practices in workplace automation.

Training Methodologies

1. Interactive Lecture and Guided Demonstration – Concepts are introduced through instructor-led discussions with live demonstrations of AI agents and n8n workflows.
2. Hands-on Workshops and Mini Projects – Participants build progressively more capable AI agents through guided exercises and practical business scenarios.

Outline
Module 1. Introduction to Agentic AI

• What is Artificial Intelligence?
• From Automation to Agentic AI
• AI Assistants vs AI Workflows vs AI Agents
• Real-world Business Applications
• Current Capabilities and Limitations

Module 2. How AI Agents Work

• The Components of an AI Agent
• Thinking, Planning, and Acting
• Inputs, Memory, Tools, and Outputs
• Single-Agent vs Multi-Agent Systems
• Human-in-the-Loop Concepts

Module 3. Understanding Large Language Models

• How LLMs Work
• Tokens and Context Windows
• Choosing an AI Model
• Local vs Cloud Models
• Prompting Principles
• Structured Outputs

Module 4. Getting Started with n8n

• Installing n8n
• Understanding the Interface
• Building Your First Workflow
• Nodes and Connections
• Executions and Debugging

Module 5. Working with Data

• Understanding JSON
• Variables and Expressions
• Data Transformation
• Conditional Logic
• Handling Errors

Module 6. Building Your First AI Agent

• The AI Agent Node
• Connecting an LLM
• Creating Effective System Prompts
• Adding Memory
• Testing Conversations

Module 7. Giving Agents Tools

• Calling APIs
• Using HTTP Requests
• Email Integration
• Reading Files
• Connecting External Services
• Triggering Automated Actions

Module 8. Basic Agent Memory

• Why Memory Matters
• Chat Memory
• Persistent Memory
• Introduction to Knowledge Bases
• Overview of Retrieval-Augmented Generation (RAG)

Module 9. Business Automation with AI Agents

• Email Assistant
• Document Assistant
• Knowledge Assistant
• Report Generator
• Approval Workflow
• Customer Support Agent

Module 10. Responsible AI

• Privacy Considerations
• Security Basics
• Human Oversight
• Hallucinations
• Validation Strategies
• AI Governance Fundamentals

Module 11. Deploying AI Workflows

• Running Workflows
• Scheduling
• Webhooks
• Sharing Workflows
• Basic Monitoring
• Troubleshooting

Module 12. Hands-on CapstoneParticipants build a complete AI assistant that:

• Accepts user input
• Uses an LLM
• Maintains conversation memory
• Uses at least one external tool
• Produces structured output
• Performs a useful business task

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