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Duration 14 hours
Course Outline
Day 1: Workflows and the AI Step
Introduction
- Determining when to use automation, AI steps, or full agents.
- Understanding n8n’s context: cloud vs. self-hosted deployments and their implications for data control.
n8n Essentials
- Core concepts: workflows, nodes, triggers, and executions.
- Manipulating data between nodes via visual field mapping, eliminating the need for syntax entry.
- Diagnosing and resolving issues by analyzing execution logs.
Connecting Apps and Data
- Utilizing webhooks and form triggers.
- Integrating spreadsheets, email, and calendar nodes.
- Managing credentials and authentication for external services.
- Mastering the HTTP Request node through step-by-step implementation.
The AI Step
- Integrating AI models into workflow logic.
- Crafting prompts to ensure consistent and reliable outputs.
- Achieving structured output and implementing automatic corrections for malformed responses.
- Classifying and extracting key information from emails, forms, and documents.
Decisions and Actions
- Implementing logic branching using If and Switch nodes.
- Designing approval steps that require human verification before executing actions.
- Logging results to spreadsheets and dispatching notifications.
Hands-on Lab: First End-to-End Workflow
- Building a complete pipeline that takes an incoming request, classifies it, records it, and routes the result.
Day 2: Agents and Operations
Agents
- Defining agents: the combination of model, memory, and tools.
- Choosing between fixed workflows and autonomous agents based on use case.
- Granting agents secure access to company documents and spreadsheets.
Agents that Act
- Differentiating between read-only and write-enabled tools.
- Defining system prompt rules: enforcing required fields, preventing data hallucination, and avoiding duplicate records.
- Stress-testing agents by attempting to break their logic.
Channels
- Setting up chat interfaces for internal team use.
- Connecting agents to specific messaging platforms.
Reliability
- Implementing error workflows, retry mechanisms, and alert notifications.
- Utilizing logs and execution history for auditing.
- Managing model usage and execution costs.
Data and Privacy
- Identifying exactly what data leaves the organization when external models are invoked.
- Demonstrating self-hosting and local model options.
- Creating a review checklist for IT and legal teams.
Building Workflows with AI
- Using AI assistants to draft initial workflow structures.
- Reviewing AI-generated drafts: verifying node functions, data sources, and empty-state handling.
Final Project and Next Steps
- Completing and presenting a custom workflow that includes an AI step and an agent tailored to a personal process.
- Developing a maintenance plan and identifying future automation candidates.
Deliverable: A fully functional workflow featuring an AI step, an agent connected to company data, comprehensive error handling, and a review checklist.
Requirements
- No programming background is required.
- Proficiency in navigating web-based applications and spreadsheets.
- Identification of at least one repetitive process in your daily work that you wish to automate.
Target Audience
- Professionals in business operations and customer-facing roles.
- Team leads and process owners.
- Non-developers aiming to build automations and AI agents using company data.
Testimonials (3)
The trainer is patient and very helpful. He knows the topic well.
CLIFFORD TABARES - Universal Leaf Philippines, Inc.
Course - Agentic AI for Business Automation: Use Cases & Integration
Good mixvof knowledge and practice
Ion Mironescu - Facultatea S.A.I.A.P.M.
Course - Agentic AI for Enterprise Applications
The mix of theory and practice and of high level and low level perspectives
