AI Automation: Build LLM Apps & AI-Agents with n8n & APIs Course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
An action-packed AI automation course that teaches you to build GPT-powered workflows and agents using n8n—perfect for modern business and productivity. This course spans approximately 6.5 hours of content across seven modules, blending foundational concepts with hands-on projects. You’ll learn to integrate large language models (LLMs) like GPT-4 into automated workflows using no-code/low-code tools, APIs, and Webhooks. By the end, you'll be able to design intelligent automation systems for lead generation, content creation, reporting, and more—all without deep coding expertise.
Module 1: Introduction to AI Automation & n8n
Estimated time: 0.5 hours
- Overview of Large Language Models (LLMs) and their role in automation
- Understanding AI agents and their practical applications
- Introduction to n8n and its visual workflow builder
- Installing and setting up n8n locally and in the cloud
Module 2: Understanding Webhooks & API Integrations
Estimated time: 0.75 hours
- Creating and managing Webhooks in n8n
- Making API calls to external services like Google Workspace and CRMs
- Connecting OpenAI API to n8n for AI-powered actions
- Handling JSON data structures in API responses
Module 3: Building Your First LLM Workflow
Estimated time: 1 hour
- Connecting GPT-4 to n8n for automated content generation
- Using dynamic inputs and variables in AI prompts
- Processing and routing AI-generated text outputs
Module 4: Creating AI Agents in n8n
Estimated time: 1 hour
- Designing multi-step workflows with memory and logic
- Chaining multiple LLM calls for complex reasoning
- Implementing dynamic task routing based on AI decisions
Module 5: Real-World Automation Projects
Estimated time: 1.25 hours
- Building a lead generation pipeline with email and CRM integration
- Creating a Notion content publishing workflow
- Automating Google Sheets report generation with AI insights
Module 6: Security, Scaling & Optimization
Estimated time: 0.75 hours
- Handling errors and implementing retry mechanisms
- Using conditional logic to improve workflow reliability
- Optimizing workflows for performance and scalability
Module 7: Deploying AI Workflows to Production
Estimated time: 0.75 hours
- Hosting n8n workflows in production environments
- Monitoring workflow execution and uptime
- Versioning workflows and team collaboration best practices
Prerequisites
- Familiarity with basic API concepts and RESTful services
- Basic understanding of JSON data format
- Access to an OpenAI API key for hands-on labs
What You'll Be Able to Do After
- Build AI-powered automation workflows using n8n and LLMs
- Integrate ChatGPT and GPT-4 into real-time business pipelines
- Automate tasks across Google Sheets, Notion, and CRM platforms
- Create intelligent AI agents that process and respond to dynamic data
- Deploy and maintain scalable AI automation systems in production