The Complete AI Agents & AI Automation Course (2025) - n8n

Explore Nan, a no-code tool for building automated workflows with a visual drag and drop builder. Start from scratch or templates on a dashboard to configure AI agents within automation.

Create an automated workflow that triggers on new emails, appends or updates rows in a Google Sheets spreadsheet, and tests the step to build an AI-enabled automation workflow.

Create your first automation by adding a trigger node, like a Gmail message received, connect credentials, set pull times, and choose full versus simplified email data.

Build an AI agent workflow in n8n using a chat message trigger, test chat, and an AI agent with a chat model, memory, and tools.

Learn how to obtain an OpenAI API key, access the API platform, and compare pricing for models like mini three, mini 4.5 preview, oh one, and oh three in Nan.

Connect the OpenAI chat model to an agent and enable window buffer memory to remember past conversations. Set a context window length to five messages.

Configure AI agent parameters with a system prompt to tailor behavior, then add tools like Google Sheet to map chat inputs to from and message columns.

Add a Gmail tool to an AI agent to automate email sending by selecting the right tool from many options, with the AI deducing subject and message from chat input.

Add the Google Calendar tool to the AI agent to automate meeting scheduling by extracting start and end times, attendees, description, and summary from chat input.

Finalize the ai agent by enabling real-time date awareness with a system message, then schedule meetings, update spreadsheets, send emails, and create calendar events using integrated tools.

Explore retrieval augmented generation (RAG) to let AI agents reference your private documents, enabling expert, private-data driven responses that integrate with your business workflows.

Create a real estate AI agent by uploading property documents to a Supabase database, then automate Google Drive downloads and enable the agent to analyze and answer questions about files.

Download files by id from a search step, retrieving the commercial and residential properties portfolios, then transfer them to a Supabase vector store using embeddings for efficient AI search.

Set up a Supabase vector store, connect to url and service key, and embed documents with OpenAI. Load data from Google Drive, create a documents table, and test the workflow.

Compare active and inactive workflows in n8n, covering test workflows, manual testing with test workflow, and automatic runs when active. Review executions and debug failures such as missing credentials.

Learn how triggers start workflows in n8n, including manual testing and automatic schedules, and discover how to configure multiple triggers to kickstart AI agent automations.

Configure Telegram triggers within an app event to start workflows on messages or channel posts. Send message contents to the AI agent node, contrasting text-based triggers with schedule triggers.

Schedule triggers run on intervals—from days to minutes—to start your workflow. Set precise times, respect rate limits, and note no data passes from the schedule trigger to the AI agent.

Use webhook triggers to start workflows from external HTTP requests when app events lack a built-in trigger, handling authentication, URLs, and retries for Shopify, Gmail, and Stripe.

Demonstrates the when executed by another workflow trigger that links a main workflow to a sub workflow and passes data like a URL to tools such as the SEO tool.

Learn how the chat trigger starts workflow steps from chat input, sends prompts to an AI agent, and compares action based triggers with text based triggers.

Learn how nodes define steps in aNan workflow, from the trigger to subsequent steps, including chat trigger and AI tools agent with long term memories.

Learn how actions inside app nodes, powered by AI agent tools, extend automation beyond triggers, using Gmail and Telegram to perform actions after a message is received within a workflow.

Explore flow nodes in n8n, including filter, if, loop, and merge, to route telegram messages, transcribe voice, process Shopify orders, and merge data with long-term memory for AI agents.

Use the HTTP request node to fetch data from APIs and access live market information. Apply API keys and header auth to perform GET requests.

Explore the AI agent's brain, the chat model, and its memory and tools, and compare OpenAI, Google Gemini, Deep Sea, and others by cost and capability.

Learn to build real AI agents for businesses using a no-code platform, enabling small and medium enterprises to automate workflows without technical knowledge.

Discover how a leads generator researches LinkedIn profiles based on your criteria (names, titles, industries, locations) and organizes and labels their contact details in Google Sheets for outreach.

Build a leads generator AI agent that extracts job title, industry, and location from requests, searches LinkedIn with Google Custom Search, cleans results, and stores leads in Google Sheets.

Manage existing leads with an AI agent that handles form submissions, crafts personalized emails, schedules meetings, updates Google Sheets, and provides daily lead summaries with value tagging.

Build a leads management AI agent that captures client details via forms, labels value by budget, emails auto replies, and logs data to Google Sheets for daily summaries.

Learn to use a social media AI agent to automatically generate two posts from a title, one for LinkedIn and one for X, and publish them across your business brands.

Explore how the AI agent structure combines live candlestick data, primary analysis, lagging indicators, and sentiment analysis to deliver forward-looking trading signals via a unified json.

Trigger a telegram message to fetch Binance candlestick data for BTC USDt and merge 15 minute, 1 hour, and 1 day candles into a single json for ai agents.

Build an AI agent workflow that fetches crypto news via News API, filters to title and description, and runs sentiment analysis with OpenAI to produce short-term and long-term sentiment scores.

Merge candlestick data with sentiment analysis into a json payload and feed it to an ai agent to generate short-term and long-term trading recommendations for spot and leverage trading.

Launch an ai agent that tracks US politician trades, considers 45-day disclosure delays, and analyzes price discrepancies to current prices, generating buy, sell, or avoid recommendations via a Telegram workflow.

Build a no-code ai agent with nan to scrape politician trades from capitaltrades.com, structure data into json, fetch stock prices via an api, and analyze trades with an ai model.

Build a politician trades ai agent that uses schedule and telegram triggers, scrapes capitaltrades.com, converts to json, extracts tickers, and fetches current prices via the financial modeling prep api.

Aggregate multiple data items into a single input, merge politician trades with live stock prices, and feed them to an AI agent to produce a concise analysis and recommendations.

Build an AI agent that scans trending Solana meme coins by 24-hour volume, transactions, and holder data, filters by market cap 1–5 million, and outputs three top picks.

Build an ai agent workflow with a telegram trigger to fetch trending solana meme coins via Morales, filter by market cap and liquidity, attach holder data, and surface top picks.

Aggregate multiple token data into a single json to feed an ai agent, define prompts, and evaluate Solana memecoins daily to output the top three buy picks via telegram.

Learn to build a sports betting AI agent in n8n that uses odds data, historical fight data, and sentiment analysis from public news to generate betting recommendations.

Build and finalize a sports betting AI agent that gathers odds, historical fighter data, and sentiment from recent news, then analyzes them to recommend a wager.

Automates a daily ai agent that summarizes the past 24 hours of cryptocurrency price action across coins using 15m/1h/1d candles, delivering insights via a formatted market report emailed every midnight.

Build and operate a central AI agent within Nan that reads and updates revenue and expense sheets, driven by a chat trigger and prompts, with receipts saved to Google Drive.

Build an accounts payable automation in n8n, processing Gmail invoices, uploading PDFs to Google Drive, extracting text with OCR, parsing data with AI, and logging to Google Sheets with reminders.

Develop and test a real estate AI agent using the Zillow API to fetch market data, compute KPIs like cash flow, cap rate, and ROI, and send daily top-property reports.

Finalize a real estate AI agent by calculating cash on cash, ROI, and expenses using a code node, then update Google Sheets daily and email a daily KPI report.

Explore a four-agent ai seo system that acts as a full seo agency, offering on-page seo analysis, keyword generation, blog post creation, and rank tracking to improve Google rankings.

Build a no-code ai agent hub that coordinates four child agents for on-page seo, keyword research, blog post creation, and rank tracking via Telegram.

Build the remaining child agents, including a keyword generator and a blog post generator, via a multi-step workflow with OpenAI GPT 4.1 mini, topic extraction, JSON outputs, and SEO-friendly blogging.

Learn two AI agents for Reddit business discovery: one collects startup ideas from subreddits and evaluates them with AI, the other uncovers niche pain points to generate ideas.

Discover how to generate thousands of high-quality leads with AI agents using Google Maps, Apify, and Apollo, all via a no-code workflow that exports data to Google Sheets.

Build and deploy a day-trader AI agent in n8n that combines minute, fifteen-minute, and hourly candlesticks with news sentiment to produce a buy, sell, or hold recommendation.

Learn to build a complete legal AI system for law firms that automates document summaries, contract analysis, memo drafting, and deadline reminders using a no-code workflow with three AI agents.