AI Agents & Automation

About this course

Who this course is for

What you'll learn

• Map a manual process into an automated workflow
• Explain how triggers, actions, and integrations connect tools
• Describe how AI agents plan tasks and use tools
• Design automations with error handling, review, and oversight

Course details

Level

beginner

Estimated duration

12 lessons · about 2.5 hours

What's included

• 12 lessons
• Progress tracking

Requirements

• No prior programming experience required.
• Basic computer and internet skills recommended.

Curriculum

1. 01

   Lesson 1: What Automation Is and Where It Helps

   Learn what automation means, how ordinary rules-based automation differs from generative AI and tool-using AI agents, and how to recognize tasks that are good, poor, or risky candidates for automation.

   12m
2. 02

   Lesson 2: Mapping a Process Before Automating It

   Discover how to document a real process step by step — including inputs, decisions, owners, exceptions, and handoffs — so that any automation you build reflects how the work actually happens.

   12m
3. 03

   Lesson 3: Triggers, Actions, and Workflows

   Learn the building blocks of rules-based automation — triggers, conditions, actions, and workflows — and how to design a simple, testable workflow that handles both the normal path and common exceptions.

   12m
4. 04

   Lesson 4: How Apps Share Data

   Understand how information moves between applications — records, fields, data types, formats, and unique identifiers — and why consistent data is the foundation of every reliable automation.

   12m
5. 05

   Lesson 5: Integrations, APIs, and Webhooks

   Learn how applications connect through APIs and webhooks, how authentication and permissions protect those connections, and why rate limits and idempotency matter for dependable integrations.

   12m
6. 06

   Lesson 6: Building a Multi-Step Workflow

   Bring triggers, data mapping, APIs, and error handling together to design a multi-step workflow, with a worked customer service triage example that includes validation, branching, retries, and human handoffs.

   12m
7. 07

   Lesson 7: What an AI Agent Is

   Learn what an AI agent is, how it differs from a chatbot and from a fixed workflow, what large language models can and cannot do reliably, and when an agent is the right choice.

   12m
8. 08

   Lesson 8: How Agents Plan, Reason, and Use Tools

   Explore how agents break goals into steps, choose and call tools, use context and memory, and why clear tool definitions, permissions, and stopping conditions keep agents reliable.

   12m
9. 09

   Lesson 9: Designing an Agent for a Task

   Apply a structured design method to scope an agent for a real task — defining its goal, users, tools, permissions, instructions, escalation rules, and evaluation tests before it is deployed.

   12m
10. 10

    Lesson 10: Error Handling and Monitoring

    Learn how automations and agents fail, how to classify errors, design retries and fallbacks, and set up logging, alerts, and monitoring so problems are noticed and fixed quickly.

    12m
11. 11

    Lesson 11: Human Review, Safety, and Governance

    Understand where human approval belongs in automated systems, how to protect privacy and security, how to manage bias and transparency, and how simple governance keeps automations accountable.

    12m
12. 12

    Lesson 12: Planning an Automation Project

    Pull the course together into a practical project plan — selecting the right opportunity, estimating value and cost, choosing between workflows and agents, piloting, measuring results, and improving over time.

    12m