Zapier & Make: Advanced

An advanced automation course for Zapier and Make: multi-step workflows with AI reasoning steps, branching logic, and robust error handling. Learners ship an automation reliable enough to run unattended.

What this course covers

The course runs across 12 topics, each one a short adaptive session rather than a recorded lecture. The tutor explains the idea, works an example, checks understanding, and adjusts the next step to the answer given.

Advanced Multi-Step Architecture in Zapier & Make — Understand how to architect complex, multi-step automations. Learn key concepts of state management, payload structure, and data mapping across multiple applications.
Hands-on: Mapping and Building Multi-Step Sequences — Build a multi-step workflow from scratch, ensuring clean data passing and field mapping between trigger and multiple action steps.
Integrating AI Reasoning and Structured Prompting Steps — Incorporate AI steps (using OpenAI or Anthropic integrations) to analyze unstructured data, make logic-based decisions, and output structured JSON for downstream actions.
Implementing Branching Logic in Zapier Paths — Configure Zapier Paths to route data dynamically based on conditional logic, AI classifications, or incoming payload values.
Advanced Routing and Filtering in Make — Utilize Make's Router module, advanced filters, and execution paths to handle complex branching logic and data manipulation.
Scenario Decision: Designing the Optimal Branching Strategy — Evaluate a complex business case and choose the most efficient, cost-effective branching architecture to minimize task/operation usage.
Error Handling Fundamentals: Retries, Alerts, and Fallbacks — Explore theoretical strategies for handling API rate limits, schema changes, and network timeouts to ensure unattended reliability.
Building Error-Resilient Zaps in Zapier — Configure custom error handling, step retries, and fallback actions in Zapier to catch failures before they halt execution.
Configuring Error Directives in Make — Implement advanced error handling directives in Make (Break, Resume, Rollback, Ignore) to gracefully manage scenario failures.
Scenario Decision: Resolving Production Runtime Failures — Troubleshoot a live, failing automation. Decide on the correct fix—such as data transformation, fallback paths, or conditional filters—under pressure.
Setting Up Real-Time Monitoring and Slack/Email Alerting — Build automated monitoring workflows that ping dedicated Slack channels or email inboxes when critical errors occur.
Final Deployment, Auditing, and Unattended Execution — Apply best practices for testing, performance auditing, and pushing your multi-step AI automation to live production to run safely unattended.

Skills you build

Results are measured against named skills in the OneRange taxonomy of more than 10,000 skills, so a manager sees proficiency per skill rather than a completion tick.

Who it is for

Ops, marketing ops, builders. The material is pitched at advanced level, and takes roughly 150 minutes at a typical pace. Because every session adapts, someone who already knows a topic moves through it quickly instead of sitting through an explanation they do not need.

It sits in the Tool: Automation track of the Vero AI Catalog, and can be assigned to one person, a team, or the whole company.

How it is delivered and assessed

Delivery is conversational and interactive, including guided lab, branching scenario exercises. There is no video to sit through and no slide deck to click past.

Understanding is checked with a lab assessment of 5 items, with a pass mark of 70%.

Administrators can copy this course into their own library and adapt it — edit the outline, change the duration, swap the assessment format, or ground it in internal documentation so answers cite the company's own source material.

Also in this track

All AI Agents training courses →
Computer-Use & Browser Agents — This course covers agents that operate software the way people do - clicking, typing, browsing. Learners build a supervised computer-use workflow and learn where the reliability boundary really sits.
AI Agents & Agentic Workflows — Learners understand and design agentic systems that take multi-step actions with tools. The course covers what an agent is, tools and function calling, multi-step and multi-agent designs, MCP and orchestration, and guardrails. Participants finish able to design agents that are useful and safe.
Agent Memory & State — A design course on giving AI systems usable memory: architectures for persistence, what to store versus retrieve, and handling privacy and staleness. Learners add durable memory to a working agent.
Orchestration Frameworks — A judgment-heavy course on orchestration tooling (LangChain/LlamaIndex-class): what it solves, what it obscures, and when plain code is better. Learners build the same workflow twice and compare.
n8n Workflow Automation — This advanced course teaches builders to create sophisticated AI automations and agents in n8n. Learners work with nodes and workflows, AI agent nodes, APIs and webhooks, self-hosting, and debugging. They leave able to ship reliable, production-grade automations.
AI Automation Assessment — AI Automation Assessment: designing and running a reliable workflow.
No-Code AI App Builder — Ship real AI-powered apps without writing code
Automating Small Tasks Pathway — Grow from automating one small task into building advanced multi-step automations.

Frequently asked questions

How long does this course take?

It runs roughly 150 minutes at a typical pace. Because every session adapts, someone who already knows a topic moves through it quickly instead of sitting through an explanation they do not need.

How is it assigned to a team?

An administrator assigns it from the Vero dashboard to one person, a team, a department or the whole company, and sees progress and results per person and per skill.

Can we customise it with our own documents and terminology?

Yes. Administrators can copy this course into their own library and adapt it — edit the outline, change the duration, swap the assessment format, or ground it in internal documentation so answers cite the company's own source material.

Course code TUL-ZAP-201.