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Duration 14 hours
Course Outline
Day 1: Workflows and the AI step
Introduction
- Determining when to automate, when to incorporate an AI step, and when to deploy an agent
- n8n in context: Comparing cloud vs. self-hosted deployments and their implications for company data
n8n Essentials
- Understanding workflows, nodes, triggers, and executions
- Transferring data between nodes by dragging fields, eliminating the need for syntax typing
- Analyzing executions to identify and resolve issues
Connecting Apps and Data
- Utilizing Webhooks and form triggers
- Working with spreadsheet, email, and calendar nodes
- Managing credentials and authentication for external services
- A step-by-step guide to the HTTP Request node
The AI Step
- Incorporating a model into a workflow
- Crafting prompts for consistent and reliable output
- Achieving structured output and automatically correcting malformed responses
- Classifying and extracting information from emails, forms, and documents
Decisions and Actions
- Implementing branching logic with If and Switch statements
- Adding approval steps to require human input before executing actions
- Writing results to spreadsheets and dispatching notifications
Hands-on Lab: First End-to-End Workflow
- Tracing the journey from an incoming request to a classified, recorded, and routed outcome
Day 2: Agents and Operations
Agents
- Defining an agent: the role of the model, memory, and tools
- Choosing between a fixed workflow and an agent
- Granting agents access to company documents and spreadsheets
Acting Agents
- Distinguishing between tools that read and tools that write
- Establishing system prompt rules: mandatory fields, preventing data fabrication, and avoiding duplicate records
- Testing agent robustness by attempting to break its logic
Channels
- Setting up chat interfaces for internal use
- Connecting agents to a single messaging channel
Reliability
- Implementing error workflows, retries, and notifications
- Reviewing logs and execution history
- Managing model and execution costs
Data and Privacy
- Identifying what data leaves the company when a model is invoked
- Self-hosting and local models: Instructor demonstration
- A checklist for review with IT or legal teams
Building Workflows with AI
- Using an AI assistant to draft initial workflow structures
- Reviewing drafts: Analyzing node functions, data sources, and handling of empty states
Final Project and Next Steps
- Participants complete and present a workflow featuring an AI step and an agent applied to their own process
- Developing a maintenance plan and identifying future automation candidates
Deliverable: A functional workflow incorporating an AI step, an agent connected to company data, error handling, and a review checklist.
Requirements
- No prior programming experience is necessary
- Proficiency with web applications and spreadsheets
- A clear understanding of one repetitive process within your own work
Target Audience
- Professionals in business, operations, and customer-facing roles
- Team leads and process owners
- Non-developers seeking 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
