AI Workflow Automation
Build, deploy, and operate AI-powered automation systems that run real business processes
8 phases. 40 lessons. 40 labs. 3 projects. The full AI workflow automation stack: automation platform fundamentals (Zapier, Make, n8n), AI-powered document processing, RAG pipelines in workflows, AI agent orchestration, Dify and visual AI builders, enterprise integration, production monitoring, and cost optimization. You build real automations that process documents, handle emails, update CRMs, and run business processes end-to-end — and graduate with a portfolio of working automation systems yo
- Lessons: —
- Labs: —
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- Level: Beginner
Curriculum
- AI Workflow Automation Fundamentals — What AI workflow automation is, the tool landscape (Zapier, Make, n8n, Dify, Flowise, Langflow), the workflow-not-model insight, when to use AI vs traditional automation, cost economics of AI calls, the automation stack from triggers to observability
- No-Code Automation Platforms — Zapier, Make, n8n — Zapier fundamentals (triggers, actions, 7000+ app ecosystem), Make.com visual scenarios (routers, iterators, operation-based pricing), n8n fundamentals (self-hosting, nodes, visual canvas, code nodes), building your first AI-powered workflow, platform selection framework
- n8n for AI Automation — n8n advanced patterns (sub-workflows, code nodes, custom JS/Python logic), AI agent nodes (LLM integration, tool calling, memory), vector stores and RAG in n8n (Pinecone, Qdrant, Supabase), webhooks and event-driven triggers, error handling and production patterns
- AI Document Processing & Data Extraction — Document AI fundamentals (OCR, unstructured data, LLM extraction), PDF processing pipelines (inbox to structured data), email parsing and classification with LLMs, structured output from LLMs (JSON schemas, function calling, validation), data validation and human-in-the-loop exception handling
- RAG Pipelines in Workflows — RAG fundamentals for automation (chunking, embeddings, vector stores), building knowledge bases in Dify and n8n, advanced retrieval (hybrid search, reranking, parent-child chunking), document Q&A automation, RAG evaluation and quality tuning
- AI Agents in Workflows — Agent fundamentals (ReAct, function calling, tool selection), building AI agents in n8n (tools, sub-workflows, agent nodes), multi-agent orchestration (coordinator and worker patterns), MCP (Model Context Protocol) for connecting agents to systems, agent guardrails and human approval gates
- Dify & Visual AI App Builders — Dify fundamentals (workflows, chatflows, visual canvas), RAG pipelines in Dify (knowledge bases, retrieval strategies), agent strategies in Dify (function calling vs ReAct), Flowise and Langflow comparison, publishing and deploying AI apps from visual builders
- Enterprise Integration, Production & Capstone — Enterprise platform integration (ServiceNow Now Assist & AI Agent Studio, Salesforce Agentforce & Flow, SAP, Microsoft Dynamics), production deployment (self-hosting, Docker, scaling), observability (logging, tracing, monitoring AI workflows), cost optimization (model routing, caching, budget management), governance and compliance, capstone end-to-end automation system
Skills You Will Learn
- n8n
- Dify
- AI Document Processing
- RAG Pipelines
- AI Agents
- MCP
- Production Automation
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