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Duration 14 hours
Course Outline
Day 1: Workflows and the AI step
Introduction
- Identifying when to automate, when to use an AI step, and when to deploy an agent
- n8n in context: comparing cloud and self-hosted environments and their implications for company data
n8n fundamentals
- Understanding workflows, nodes, triggers, and executions
- Transferring data between nodes by dragging fields, eliminating the need for syntax entry
- Analyzing execution logs to identify and resolve issues
Connecting apps and data
- Utilising webhooks and form triggers
- Working with spreadsheet, email, and calendar nodes
- Managing credentials and authentication for external services
- A step-by-step walkthrough of the HTTP Request node
The AI step
- Integrating a model into a workflow
- Crafting prompts to ensure reliable outputs
- Achieving structured output and automatically correcting malformed responses
- Classifying and extracting information from emails, forms, and documents
Decisions and actions
- Implementing branching logic using If and Switch nodes
- Establishing approval steps: requesting human input before executing an action
- Recording results in spreadsheets and dispatching notifications
Practical lab: first end-to-end workflow
- Transitioning 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 internal documents and spreadsheets
Agents that act
- Distinguishing between read-only tools and write-capable tools
- Defining system prompt rules: enforcing required fields, preventing invented data, and avoiding duplicate records
- Testing agent robustness by attempting to introduce errors
Channels
- Setting up a chat interface for internal use
- Connecting the agent to a single messaging channel
Reliability
- Configuring error workflows, retries, and notifications
- Reviewing logs and execution history
- Managing model usage and execution costs
Data and privacy
- Assessing what data leaves the organisation when a model is invoked
- Self-hosting and local models: instructor-led demonstration
- Creating a checklist for review with IT or legal teams
Building workflows with AI
- Using an AI assistant to draft a workflow
- Reviewing the draft: understanding node functions, data sources, and handling of empty data scenarios
Final project and next steps
- Each participant completes and presents 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 linked to company data, error handling, and a review checklist.
Requirements
- No prior programming experience is necessary
- Familiarity with using web applications and spreadsheets
- A clear understanding of one repetitive process within your current role
Audience
- Professionals in business, operations, and customer-facing roles
- Team leaders and process owners
- Non-developers interested in building 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
