Master
n8n & Automation

Introduction to n8n and process automation

Understand the no-code automation ecosystem, real business use cases, and how n8n compares to alternatives (Make, Zapier). A big-picture view of what workflows can do.

Installing and configuring n8n

Install n8n locally, configure the essential environment variables, create your account, and access the editor.

Understanding the n8n interface and basics

Navigate the workflow editor, explore the node catalog, understand the JSON data model, and run your first workflow end to end.

Building workflows and managing triggers

Master the triggers: manual, Webhook, Schedule (cron), and event-based. Understand flow logic and conditional branching (IF, Switch).

Understanding Data Transformation nodes

Use the Set, Function, Merge, and Split In Batches nodes along with n8n expressions to filter, restructure, and transform JSON data between workflow steps.

Reliability and error handling

Make a workflow reliable once nobody is watching it: automatic retries on failure, an Error Trigger workflow that alerts you the moment an execution fails, fallback branches, reading past executions to diagnose and re-run, and idempotency so a webhook fired twice doesn't send two emails.

Connecting workflows to Google tools

Set up OAuth2 with Google, read and write to Google Sheets, create and manage Google Calendar events, and send emails via Gmail — all from an n8n workflow.

Building and using APIs with Webhooks

Expose HTTP endpoints from n8n via the Webhook node, secure incoming calls, consume third-party APIs with HTTP Request, and handle authentication (API Key, Bearer, Basic Auth).

Building an interface to trigger a workflow

Build a simple web form (HTML/JS) or use n8n's Form node to create a user interface that launches workflows with custom parameters.

Scraping and data collection with n8n

Extract content from web pages with the HTTP Request and HTML Extract nodes, scrape structured data lists, and store the results in a database or file.

Using different AI models (LLM and Vision)

Explore the different LLM and Vision models available in n8n. Use multimodal capabilities to analyze images, screenshots, or visual documents within a workflow.

Introduction to AI agents and system prompts

Understand the difference between a simple LLM call and an autonomous agent. Configure n8n's AI Agent node, write effective system prompts, and freely choose your preferred model.

Connecting tools to an AI agent

Connect tools to an agent: web search, sending email, reading a database, API calls. Understand how the agent selects and chains actions together.

Understanding MCP servers

Introduction to the Model Context Protocol (MCP), how it differs from classic tools, configuring an MCP server in n8n, and exposing it to an AI agent to extend its capabilities.

Running commands on the host machine

Use the Execute Command node to run shell scripts, interact with the operating system, and orchestrate external processes from n8n.

Working with the host machine's disk

Read, write, and move files on the local file system, process CSV, PDF, or image files, and integrate these capabilities into automated workflows.

Building a Telegram AI agent (voice communication)

Build a Telegram bot connected to an AI agent: receive text and voice messages, generate intelligent replies, and send them back as audio via TTS.

Understanding RAG system theory

Retrieval-Augmented Generation architecture: chunking → embedding → vector storage → retrieval → generation pipeline. Use cases and advantages over fine-tuning.

Building a vector database with Supabase

Set up Supabase and its built-in Vector Store (pgvector), create vector tables, understand indexes and cosine similarity search, and integrate the database into an n8n workflow.

Using embedding models

Understand what embeddings are, use different embedding models of your choice, and generate and store vectors in Supabase from n8n.

Building a knowledge base

Ingest documents (PDF, Notion, web pages) into a complete RAG pipeline: parsing, chunking, embedding, and vector indexing — all automated with n8n.

Building an AI agent that uses a knowledge base

Connect the vector database to an n8n agent to create an assistant that can answer from your own documents, with source citations and conversation memory.