n8n Masterclass: Build AI Automations & Scalable Workflows

master n8n by focusing on 13 core nodes—the 20% that delivers 80% of results—after environment setup, enabling you to build scalable automations quickly.

Explore execution essentials in n8n, including sequential, synchronous node runs, top-down flow order, triggers like webhook and time-based ones, per-input execution, and branching with conditions.

Learn how to use basic triggers in n8n, including manual, schedule (cron), and app events, to activate and test workflows with OneDrive and Google Sheets, and apply universal data processing.

Learn universal data processing with n8n: flatten nested leads data, split and aggregate rows, and manipulate fields using set, if, and code nodes for scalable workflows.

build scalable workflows with http requests and APIs in n8n, using endpoints, get and post methods, headers, bearer authentication, and webhooks.

Store and organize manipulated data by creating or selecting a storage sheet in Google Sheets or Airtable, append rows, auto-map columns, and handle new fields as needed.

Learn to integrate ai into workflows using the lm chain, choose ai nodes for judgment, and leverage structured outputs and output parsers for reliable sentiment analysis and tool access.

Plan effective workflows by breaking large problems into small steps, identifying triggers, data sources, inputs, transformations, and outputs, and visualizing with simple workflow diagrams.

Map your workflow end-to-end using sticky notes, markdown notes, and mock nodes to plan inputs, outputs, and the path from CV input to CRM upload in n8n.

Detect CV input format as PDF or image, then extract text from images. Standardize and merge data across inputs and upload to CRM with conditional routing.

Explore building scalable workflows in n8n by standardizing contact data from text or OCR inputs and routing to a CRM like HubSpot using triggers, if/switch logic, and LLM extraction.

Master AI fundamentals for automation, including LLMs, prompts, tokens, and tool connectors; learn how AI agents differ from LLMs via the model context protocol (MCP).

Structure a content calendar in n8n by creating a calendar tab with topic, date scheduled, content, and status, and automate content generation using Google Sheets triggers and brand guidelines.

Connect to Google Sheets by loading a sheet via URL and sheet ID, trigger on row additions, and pull topic data such as AI agents from the header.

Build a LinkedIn content system that uses AI to generate posts and images from a Google Sheets plan, applying brand guidelines and enabling manual review before automated scheduling.

Bring brand inputs and guidelines by fetching a row with a Google Sheets node, authorizing credentials, and executing the workflow to generate AI-driven content and output results to Google Sheets.

Set up a Google Sheets output in n8n to append or update rows using a unique id, map date created, topic content, and status, and format today's date.

Build scalable ai content workflows using an ai content generation node: input topics, prompt-based llm chain, brand guidelines, structured json output, openrouter models, and loop node.

Apply loop logic to process items one at a time, filter blanks early, generate topic content with AI, and write results to a Google Sheet while protecting drafts.

Learn to generate images with DALL-E 3 in a node-based workflow using OpenAI, including managing API keys, testing connections, and hosting images via image BB for URL storage.

Create scalable AI-powered workflows that generate content and host images, from topic input and LLM-driven post creation to image hosting and publishing on LinkedIn.

Automate LinkedIn posting with a daily workflow that pulls Google Sheet data, filters by approved and today, and posts via upload post with optional images.

Build your authentic voice with a complete tone of voice brief. Use two documents—the tone of voice brief and tone of voice examples—and guide AI to write in your style.

Learn to reverse engineer a million-dollar seo SaaS by building six workflows that pull everything together inside Nan and Airtable to create a complete seo content system.

Create high quality seo optimized blog articles with long-tail keywords, internal linking, and engaging content like diagrams and videos to boost on-page time, using scalable n8n workflows.

Outlines a two-milestone workflow: build a visual Airtable back end with interfaces and content creation flows, then migrate to a front end with Supabase authentication and database.

Set up scalable n8n workflows by emulating best-in-class inputs and outputs, generate keyword-optimized blog content with Airtable-backed repositories and schedules, and enable authenticated front-end publishing.

Link company and competitor data in Airtable with URL fields and relational records to power a scalable workflow for automated blog inputs and branding guidelines.

Build a keyword research infrastructure that automatically generates SEO keywords, analyzes competition, volume, CPC, and keyword difficulty, and plans blog content with brand text realism and watercolor realism.

Create a new block content table in Airtable linked to the keywords table, with a block id, date scheduled, and both non-rich and rich blog content for SEO workflows.

Construct a scalable workflow in Nan that maps inputs—branding details, company data, competitors, keywords, and blog content—into outputs like keywords, blog articles with embedded videos, infographics, images stored in Airtable.

Set up an Airtable base and button-triggered webhook to run the ICP generator, producing product descriptions, ICPs, pain points, and goals via an AI agent.

Execute a competitor research workflow by aligning ICP and competitor site data to identify and rank keywords for your blog content, using data for SEO via a webhook and Airtable.

Discover how to extract keywords for a URL, generate long-tail subtopics, and use data for SEO endpoints, autocomplete, and related keywords to build scalable SEO workflows.

Encode login credentials with base64 and use basic authorization to fetch live keywords for a URL. See competition, search volume, and CPC per task for scalable SEO content.

Generate long tail keywords from seed keywords using four data for seo endpoints, then group, assign to automake, and plan blog topics with generated subtopics in Airtable.

Load seed keywords, map them to company and URL records, and build a modular workflow that fetches related keywords, updates Airtable, and generates long-tail keywords with links to competitors.

Set up a modular keyword hierarchy by generating long-tail keywords from seed keywords for multiple companies and URLs using Airtable workflows. Organize progress and build hub-and-spoke topics for SEO.

Identify seed keywords and hub-and-spoke content clusters, surface long-tail subtopics and topics for SEO, manage status updates in Airtable, and generate subtopics via automated workflows.

Design a scalable content creation workflow in n8n that links seed and long-tail keywords to subtopics, generates icp-aligned blog posts with citations, images, and interlinks.

Set up workflow inputs and outputs. Pull subtopics, ICP, and style inputs, linking records to automate blog content at scale.

Set up a research agent to select topics, gather high-quality, cited sources, and plan blog content with prompt generators, lm chains, planning and writing models, and perplexity powered research.

Select ai models for scalable workflows using a reasoning-focused planning model. Build a modular content plan with planning, research, and content agents to generate structured articles, headers, and research questions.

Learn to build a content planner agent using a prompt generator, specifying inputs like ICP, subtopic, keyword, semantic variations, and outputs with structured headers and research questions for SEO.

Test and validate the content planner’s output for the AI automation course, ensuring the research agent and content agent produce clear, keyword-rich, well-structured content with strong supporting elements.

Build and optimize a research agent within ai automation workflows, running iterative research and content planning to generate sourced facts with sources for a cohesive blog.

Explore recent ai automation growth statistics, real-world use cases, and in-demand skills, then optimize research outputs with structured prompts, citations, and model choices to empower content writing.

Design a modular content writing agent using selective language models, multi-model orchestration, and system prompts to output human-like markdown content for scalable workflows.

Test content outputs to identify underperformance and problems in long-form generation. Propose section-by-section processing with research inputs and merged results to increase word count and improve context.

Explore building scalable ai-driven workflows with n8n by adding contextual awareness through looped processing, passing previously written content to the content agent to ensure flow and avoid repetition.

Learn how to build and optimize ai-driven blog content, from a structured article with links and tables to markdown rendering, and publish via Airtable with humanized writing.

Develop a client-ready blog workflow by combining AI-generated content, human edits, image generation with flux, and Airtable front-end interfaces for scheduling and publication.

Remove hardcoded values by enabling an optional selected subtopic input and dynamic topic selection in the content planner. If no subtopic is selected, randomly choose one from available subtopics.

Learn to dynamically select content style in ai-driven workflows by using a content planner to switch between informative and listicle formats, with user overrides and logic-driven defaults.

Learn to upload blog content to Airtable by updating article status, moving content to the blog content table, and using aggregation to publish the latest version.

Compare AI models for content planning, reasoning, and creative writing, prioritizing Gemini 2.5 Pro as main and Claude 3.7 Sonnet as backup, with Gemini 1.5 Flash for research.

Improve context storage in workflow data by using get workflow static data to accumulate article content in memory for the content agent, avoiding external databases.

Build an image generation workflow to embed blog images using nano banana (gemini flash 2.5) with Hugging Face and flux models, generate, edit, and host visuals for articles.

Optimize images for web performance by reducing file size with a smush it service, achieving about 67% smaller images and embedding the resulting URLs into the blog after content generation.

Create a sub workflow that can generate images and return them to an AI agent, enabling a variable image count based on blog length and embedding image URLs in markdown.

Finalize nano banana integration to generate and embed three images into blog content, linkable via Airtable, and streamline the workflow with open router prompts and brand templates.

Explore how to build a client-friendly Airtable interface to simplify data entry, view, and workflow automation, including company info, blog inputs, keywords, ICPs, and article generation.

Create a mobile-optimized company information page as a record review, selecting fields such as URL, ICP button, goals, and objectives, and sort by company name for a single company.

Explore configuring a client view and creating a flexible input interface to add and edit company records, competitors, and blog inputs, with editable fields, filters, and keyword generation.

Group keywords by company and url, sort by seed keyword, and use color cues to manage ai automation keywords; enable inline editing and record detail view for keywords.

Learn to manage seed keywords, long-tail keywords, reveal subtopics, and generate articles using the generate article view that shows keyword volume, difficulty, and content style linked to blog content.

Create filtered views to generate articles from keyword subtopics, manage article status, and enable inline editing and content style for easier article generation.

Explore building a blog content gallery view with grid and calendar styles, filtering posts by company and displaying keyword-driven subtopics and statuses.

Build a calendar-based scheduling page for blog content with date scheduled, end date, and month view filters, enabling inline edits, drag-and-drop rescheduling, and content expansion for articles, summaries, and keywords.

Generate seed keywords and long-tail keywords for competitors using a record review interface, enabling quick filtering by company and status to optimize keyword research.

Debug long-tail keyword workflow by validating seed keyword updates, handling the webhook and executions, and ensuring long-tail status completes and disappears from the page, with safeguards against double updates.

Explore prompt engineering to beat AI content detection while building human readable, engaging articles. Learn practical deep research, natural language patterns, and SEO-first prompts that boost readability and page quality.

Refine prompts with style and brand color to produce branded blog images, isolate workflow data for parallel runs, and add a main image field with a list view for V1.

Celebrate your progress building scalable workflows with n8n and explore benefits like integrations, internal linking, front end additions, and back end databases.