About AI Automation
AI automation is the skill of turning repetitive business work into workflows that run
on their own, using AI agents, APIs, and no-code tools. This course follows the order
most people learn it in. It starts with Automation Fundamentals
(mapping a process, triggers, actions, and where automation pays off), then
APIs, Webhooks & JSON so you understand how tools talk to each
other.
Next comes No-Code Automation Platforms: building real workflows in
Zapier, Make, and n8n. From there, Working with LLMs covers prompt
design, structured outputs, and function calling, while
Data & Integrations connects your workflows to spreadsheets,
CRMs, email, and chat tools.
Knowledge & RAG covers embeddings, vector databases, and
question-answering over your own documents, and
Building AI Agents covers tool use, memory, planning, and multi-step
agents that decide what to do next.
Finally, Business Use Cases applies it all to lead qualification,
document processing, and customer support, Reliability & Guardrails
covers error handling, evaluation, and human-in-the-loop approvals, and
Deploying & Monitoring covers hosting, cost control, and
measuring results: the skills that separate a clever demo from an automation a
business can trust.
Content
10 modules
01
Automation Fundamentals
Mapping a business process, spotting what is worth automating, and understanding triggers, actions, and conditions.
Workflow MappingTriggers & ActionsROI
02
APIs, Webhooks & JSON
How apps exchange data: reading API docs, making requests, handling authentication, and receiving events through webhooks.
REST APIsWebhooksJSON
03
No-Code Automation Platforms
Building multi-step workflows visually with Zapier, Make, or n8n, including branching, loops, and scheduled runs.
ZapierMaken8n
04
Working with LLMs
Calling language models from workflows: writing reliable prompts, getting structured output, and using function calling.
Prompt DesignStructured OutputFunction Calling
05
Data & Integrations
Connecting workflows to the tools businesses already use, and cleaning and transforming data as it moves between them.
Google SheetsCRMEmail & Slack
06
Knowledge & RAG
Giving AI access to your own documents with embeddings and vector search, so answers are grounded in real company data.
EmbeddingsVector DatabasesRAG
07
Building AI Agents
Designing agents that plan, call tools, remember context, and complete multi-step tasks, from single agents to small teams of them.
Tool UseAgent MemoryMCP
08
Business Use Cases
Applying everything to real work: qualifying leads, extracting data from invoices, triaging support tickets, and drafting replies.
Lead QualificationDocument ProcessingSupport Triage
09
Reliability & Guardrails
Making automations safe to trust: retries and error handling, testing AI outputs, and adding human approval where it matters.
Error HandlingEvaluationHuman-in-the-Loop
10
Deploying & Monitoring
Hosting your workflows, controlling model costs, logging runs, and measuring the time and money an automation actually saves.
Self-HostingCost ControlRun Logging
What You Can Do After This Course
By the end of the curriculum you'll have worked through 5 hands-on projects and
covered the core of what an AI automation role or freelance practice expects.
Concretely, you'll be able to:
Find what to automate: map a business process, spot the repetitive steps, and estimate the time and cost saved.
Connect any tool: read API docs, send requests, and trigger workflows from webhooks and JSON data.
Build workflows without code: design multi-step automations in Zapier, Make, or n8n with branching and error paths.
Put LLMs to work: write dependable prompts, get structured output, and let models call tools inside your workflows.
Ground AI in your data: build retrieval pipelines so assistants answer from your own documents instead of guessing.
Build AI agents: create agents that plan, use tools, and complete multi-step tasks for sales, operations, and support.
Run it in production: add guardrails and human approvals, host your workflows, control costs, and monitor results over time.