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The Complete n8n Masterclass: Build Agentic AI Workflows

Name: The Complete n8n Masterclass: Build Agentic AI Workflows
Rating: 5.0 (6 reviews)

Beginner to Advanced in 2026 — Build AI Agents, Multi-Agent Systems, RAG, Generative AI Workflows and No-Code Automation

Hot & New

New

Created byAshwin Goyal

Last updated 5/2026

English

What you'll learn

Build production-ready AI agents and agentic AI workflows in n8n from scratch — no coding required, even if you've never automated anything before.
Master n8n end-to-end: triggers, nodes, webhooks, HTTP requests, API integrations, branching logic, loops, error handling, and self-hosting.
Build a complete RAG system from scratch with chunking, embeddings, vector databases, and semantic search over your own knowledge base.
Design multi-agent systems using supervisor-and-worker architectures, sequential agents, and advanced context handoff between agents.
Ship 15+ real-world workflows: lead gen pipelines, support triage, invoice extraction, RAG assistants, financial news aggregators, and more.
Apply prompt engineering, agent memory, tool use, and autonomy patterns the way production-grade AI agents actually use them.
Build self-healing automations with centralized error handling, guardrails, logging, and human-in-the-loop checkpoints for production reliability.
Integrate n8n with the apps you already use — Google Sheets, Telegram, Gmail, Slack, CRMs, and 500+ other services.
Launch your own AI Automation Agency or freelance practice with a portfolio of working agentic AI workflows you can sell to real clients.

Course content

10 sections • 27 lectures • 7h 2m total length

Introduction2:32
By the end of this lecture, you'll know exactly what to expect in this course and learn a bit about me.
Generative and Agentic AI3:15
By the end of this lecture, you'll have a clear, jargon-free understanding of what AI actually is, how modern LLMs work, and why this matters for everything you'll build in the course.
You would also be able to explain the difference between generative and agentic AI.

Introduction to n8n7:04
By the end of this lecture, you'll understand what n8n is, why it has become the leading AI workflow automation platform, and how its node-based visual builder works.
Structure of an n8n workflow4:47
By the end of this lecture, you'll be able to read any n8n workflow at a glance — triggers, nodes, data flow — and start designing your own.
n8n vs Zapier vs Make2:33
By the end of this lecture, you'll know exactly when to use n8n, when Zapier or Make is the better choice, and why n8n is the only serious option for AI agents and complex agentic workflows.
AI Agents Introduction4:21
By the end of this lecture, you'll know how n8n's AI Agent node works, what tools and memory mean inside n8n, and how the agent architecture you'll build later fits together.
AI Agents: ReAct framework, types of agents and agentic architectures9:52
By the end of this lecture, you'll understand the four pillars of agentic AI (autonomy, memory, tool use, goal-seeking) and the core design patterns: ReAct, Planning, and other types of agents.

Basic Data Pipeline: n8n form to mock CRM13:53
By the end of this lecture, you'll have built your first complete workflow that captures form submissions and pushes structured data into a CRM.
Automating Lead Generation: Google Form to Mock CRM21:36
By the end of this lecture, you'll be able to build workflows that route data dynamically from a Google form, and publish content to a Google Sheets CRM.
Automated Social Media Pipeline: Advanced Routing & Branching Logic22:12
By the end of this lecture, you'll be able to build workflows that capture user's input from a webhook, branch based on conditions, route data dynamically, and publish content to multiple destinations based on user's request.

AI Support Triage: LLMs, Prompts, Tools & Email-to-Database37:19
By the end of this lecture, you'll have built a complete support triage system that monitors an inbox, classifies tickets using an LLM, applies prompt engineering for consistent results, and writes structured records into a database — fully autonomously.
Invoice Data Extraction Agent: Forcing Strict JSON Schemas23:16
By the end of this lecture, you'll be able to extract structured data from messy unstructured documents (invoices, contracts, emails) and trust the output enough to push it directly into downstream systems.

RAG and Real-World Architectures17:57
By the end of this lecture, you'll understand what RAG is, why it solves the biggest limitation of LLMs (knowledge cutoff and hallucination), and the architectures used in production by major companies.
Knowledge Base: The Foundation of RAG2:34
By the end of this lecture, you'll know what a knowledge base actually is in the context of RAG, how to structure documents for retrieval, and what makes a knowledge base reliable vs broken.
Vector Embeddings: Numerical Representations of Words, Phrases & Documents4:16
By the end of this lecture, you'll understand how text gets converted into vectors, and why high-dimensional embeddings capture meaning.
Chunking: Fitting Text into Manageable Pieces for Retrieval3:54
By the end of this lecture, you'll know the major chunking strategies (fixed-size, recursive, semantic, document-based), when to use each, and why bad chunking is the #1 cause of broken RAG systems.
Memory: Advanced Memory Strategies for AI4:24
By the end of this lecture, you'll understand the difference between short-term, long-term, and episodic memory in AI systems, and how to design memory layers that scale across thousands of conversations.
Semantic Search: Finding Meaning, Not Keywords6:14
By the end of this lecture, you'll know how semantic search differs from keyword search, how vector similarity works under the hood, and how to combine both for hybrid search systems.

Build Your First RAG Workflow23:17
By the end of this lecture, you'll have built a complete RAG workflow that ingests documents into a vector database, retrieves relevant context based on user queries, and generates accurate answers grounded in your own data. We will also see a Pinecone-based RAG implementation in n8n.
Telegram RAG Assistant: Conversational Bots with Advanced Retrieval28:50
By the end of this lecture, you'll have deployed a production-style RAG assistant on Telegram that handles multi-turn conversations, remembers context across messages, and pulls accurate answers from your own knowledge base.
Financial News Agent: Scheduling RAG Updates from RSS Feeds23:05
By the end of this lecture, you'll be able to keep any RAG knowledge base automatically up-to-date by ingesting RSS feeds on a schedule — the pattern behind every always-fresh AI assistant in production.

Multi-Agent Marketing Team: Supervisor & Worker Architecture31:04
By the end of this lecture, you'll have built a complete multi-agent system across three connected workflows: a Supervisor agent that breaks down marketing tasks, plus two specialized Worker agents that execute and report back, followed by a QA agent that improves the content. You'll see exactly how production-grade multi-agent systems coordinate.
Cultural Travel Concierge: Sequential Agents & Context Handoff31:29
By the end of this lecture, you'll be able to design agent pipelines where each agent specializes, hands off cleanly to the next, and preserves context through complex multi-step tasks — the gold standard for reliable agent systems.

Centralized Error Handling & Self-Healing Pipelines1:03:18
By the end of this lecture, you'll have built two interconnected workflows: a Centralized Error Handler that catches failures across every other workflow, logs them, and routes alerts; plus a Self-Healing Recovery Pipeline that automatically retries, recovers, or escalates based on failure type — turning your demos into production systems.
Course Conclusion and Next Steps3:42
By the end of this lecture, you'll know exactly what to do next, how to build a solid portfolio and how to keep your skills sharp as n8n evolves.

Requirements

No coding experience or n8n exposure required. Everything is taught from the ground up in plain English with full visual explanations
A computer, an internet connection, and a free n8n account (you'll set this up in the first section)

Description

Stop watching tutorials. Start shipping AI agents.

7 hours. 15 workflows. Zero filler.

n8n is the open-source AI workflow automation platform that's quietly become the #1 tool for building AI agents, agentic AI workflows, and generative AI automations in 2026. 187k+ GitHub stars. $1B+ valuation. Used inside Fortune 500 companies. n8n is where serious builders go for building enterprise AI workflows.

This course is 95% hands-on. You'll build real workflows from the first lecture. Concepts like webhooks, APIs, LLMs, prompt engineering, structured outputs, RAG, vector databases, multi-agent architectures, and error handling get taught the moment you need them inside a real project. No three-hour theory dumps. No watered-down demos. Real builds. Real outcomes. Workflows you can ship on day one.

Beginners welcome. Developers welcome. Marketers, ops leads, entrepreneurs, product managers — all welcome. The course meets you where you are and takes you to advanced.

What you'll build in 7 hours

A list of working systems, not topics:

A Lead Generation & CRM Pipeline with webhook capture, enrichment, and full API chaining
An Automated Social Media Publishing Pipeline with advanced routing and branching
A Support Triage Workflow powered by LLMs that classifies, routes, and responds to tickets autonomously
An Invoice Extraction Pipeline that forces strict JSON schemas from LLMs for reliable structured outputs
A Netflix Ratings AI Agent with tools, memory, and full agent autonomy
A complete RAG System from scratch — chunking, embeddings, vector stores, semantic search
An Enterprise QA Assistant on Telegram with advanced retrieval and conversational memory
A Financial Market News Aggregator that pulls RSS feeds and updates your RAG knowledge base on a schedule
A Multi-Agent Marketing Team using a supervisor-and-workers architecture with subworkflows
A Cultural Travel Concierge showing advanced context handoff and sequential agent design
A Centralized Error Handler & Self-Healing Pipeline with guardrails, logging, and production-grade reliability

Topics covered (deeply, through practice)

n8n fundamentals · Visual workflow builder · Triggers & nodes · Webhooks · HTTP requests · API integrations · Authentication & credentials · Data transformation · Conditional logic · Routing & branching · Loops · Merge logic · LLM integrations (OpenAI, Claude, Gemini, Ollama, DeepSeek) · Prompt engineering · Structured outputs · JSON schemas · AI agents · Agent tools & autonomy · Agent memory · RAG · Chunking strategies · Embeddings · Vector databases (n8n Simple Vector Store, Pinecone) · Semantic search · Knowledge bases · Multi-agent architectures · Supervisor-worker patterns · Sequential agents · Context handoff · Subworkflows · Error handling · Guardrails · Logging · Self-healing workflows · Production deployment · No-code automation · Generative AI workflows · Agentic AI workflows · AI workflow automation

Why this course works

95% hands-on by design. You build from lecture one. Theory shows up only when you're about to use it.

No coding required. If you can drag, drop, and read English, you can finish this course.

Built for 2026. Every workflow uses current n8n AI agent nodes, LLM APIs, current vector database integrations.

Real systems, not toy demos. Every project is something you'd put in front of a paying client or deploy at work tomorrow.

Multi-role friendly. Whether you want to automate your own life, build internal tools, freelance, or launch an AI Automation Agency — the workflows transfer directly.

Future-proof. Agentic AI is the biggest shift since cloud. n8n is leading it. You'll be in the right place at the right time.

Who this course is for

Complete beginners with zero automation or AI experience who want a clear, project-led path in
Developers and engineers who want to ship AI agents without writing thousands of lines of LangChain code
Marketers, salespeople, and operations professionals who want to automate the repetitive work eating their week
Entrepreneurs and freelancers building (or wanting to build) an AI Automation Agency
Product managers, founders, and team leads evaluating agentic AI for production use
Existing n8n users who've stuck to basic workflows and want to level up to AI agents, RAG, and multi-agent systems
Anyone tired of consuming AI content and ready to actually build something with it

Prerequisites

A computer. An internet connection. Curiosity. That's it. No coding background. No prior n8n experience. Everything is taught from the ground up.

What you walk away with

A portfolio of 15+ production-ready AI workflows. The confidence to architect agentic AI systems from scratch. A clear sense of when to use a simple automation, when to reach for an AI agent, and when you actually need a multi-agent swarm. Enough technical fluency to talk to engineers, enough practical skill to ship without them, and the strategic perspective to know what to build next.

This is the n8n course you wished existed the first time you heard the words "AI agent."

Enroll now. Build your first agent today. Ship your first multi-agent system this week.

Lifetime access. 30-day money-back guarantee. Future updates included as n8n evolves through 2026 and beyond.

Who this course is for:

Complete beginners who want a clear, hands-on path into AI agents, agentic AI, and workflow automation in 2026
Existing n8n users stuck on basic workflows who want to level up to AI agents, RAG, and multi-agent systems
Anyone tired of consuming AI content and ready to actually build, ship, and deploy something real with it

The Complete n8n Masterclass: Build Agentic AI Workflows

What you'll learn

Explore related topics

Course content

Introduction2 lectures • 6min

Basics of n8n and AI Agents5 lectures • 29min

Setting up your n8n workspace1 lecture • 3min

The Visual Backend: Zero to Automation3 lectures • 58min

AI Integration — Connecting the Brain2 lectures • 1hr 1min

AI Agents with Tools & Memory1 lecture • 23min

RAG and Related Concepts6 lectures • 39min

Building Production RAG Systems — From Knowledge Base to Conversational AI3 lectures • 1hr 15min

Multi-Agent Systems2 lectures • 1hr 3min

Production Readiness and Course Wrap-Up2 lectures • 1hr 7min

Requirements

Description

Who this course is for: