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Duration 14 hours
Course Outline
Day 1: Workflows and the AI step
Introduction
- Determining when to automate, when to use an AI step, and when to deploy an agent
- Understanding n8n in context: comparing cloud and self-hosted deployments and their implications for corporate data
n8n essentials
- Key concepts: workflows, nodes, triggers, and executions
- Transferring data between nodes by dragging fields, eliminating the need to type syntax
- Analyzing execution logs to identify and resolve issues
Connecting apps and data
- Utilizing Webhooks and form triggers
- Integrating spreadsheets, 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 the workflow
- Crafting prompts to ensure reliable output
- Handling structured output and automatically correcting malformed responses
- Classifying and extracting insights from emails, forms, and documents
Decisions and actions
- Implementing branching logic using If and Switch nodes
- Incorporating approval steps: requiring human sign-off before executing actions
- Recording results in spreadsheets and dispatching notifications
Hands-on lab: first end-to-end workflow
- Processing incoming requests to produce classified, recorded, and routed outcomes
Day 2: Agents and operations
Agents
- Defining an agent: the role of model, memory, and tools
- Choosing between a fixed workflow and an agent
- Granting an agent access to corporate documents and spreadsheets
Agents that act
- Distinguishing between tools that read and tools that write
- Setting system prompt rules: enforcing required fields, preventing fabricated data, and avoiding duplicate records
- Stress-testing an agent by attempting to break it
Channels
- Implementing a chat interface for internal use
- Integrating the agent with a single messaging channel
Reliability
- Configuring 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
- Exploring self-hosting and local models: instructor-led demonstration
- Using a checklist for review with IT or legal teams
Building workflows with AI
- Using an AI assistant to draft a workflow
- Reviewing the draft: analyzing each node's function, 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 functioning workflow including an AI step, an agent connected to company data, error handling, and a review checklist.
Requirements
- No programming experience is necessary
- Proficiency with web applications and spreadsheets
- A clear understanding of one repetitive process within their own role
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
