Intermediate

Building Effective AI Agents with n8n

Learn to build and deploy effective AI Agents with n8n.

4h 30m
35 lessons

Last updated: January 2026

Building Effective AI Agents with n8n
35 lessons
4h 30m of content
Certificate of completion
Community access

Course Curriculum

8 modules • 35 lessons • 4h 30m total

1
Preparations

3 lessons • 15m

Course Introduction
3:16
Setting up n8n and OpenRouter
4:10
Importing n8n Workflows
8:07
2
Building Agentic Systems

5 lessons • 37m

Introduction to Agentic Systems
7:27
Building AI Workflows
13:54
Exercise
Building AI Agents
15:58
Exercise
3
Context Engineering for AI Agents

4 lessons • 28m

Introduction to Context Engineering
5:15
AI Agent Architecture & System Prompts
10:17
Tuning an Agent's Tool Descriptions
8:08
Exercise
5:17
4
Augmented AI Agents

6 lessons • 1h

Tool Calling for AI Agents
9:05
MCP for AI Agents
14:10
Reasoning LLMs
3:35
Agentic RAG Overview
5:36
Agentic RAG - Indexing
12:52
Agentic RAG - Customer Support
14:48
5
Building Multi-Agent Systems

4 lessons • 20m

Introduction to Multi-Agent Systems
1:51
Benefits of Multi-Agent Systems
2:36
Building an Multi-Agent RAG System
8:47
Testing the Customer Support Agentic RAG System
7:29
6
Evaluating AI Agents

4 lessons • 29m

Introduction to AI Agent Evaluation
3:04
Building an Evaluation Dataset
7:29
Selecting Metrics for AI Agent Evaluation
4:16
Evaluating a Customer Support Agent
14:15
7
Optimizing AI Agents

4 lessons • 35m

Optimization Strategies and Memory
8:16
Building Guardrails for AI Agents
7:46
Model Selection
7:10
Optimizing Latency for AI Agents
12:35
8
Deploying Agentic Apps

5 lessons • 43m

Introduction to Deploying Agents and Webhooks
7:09
LLM Routing for AI Agents
6:19
Persistent Storage for AI Agents
10:49
Building Agentic Applications
15:19
Deploying Agentic Applications
3:33