OneRange

Zapier & Make: Core

Learners automate workflows that call AI across their apps with no code using Zapier and Make. The course covers triggers and actions, AI steps, multi-app workflows, and error handling. Participants finish able to remove repetitive work without engineering help.

What this course covers

The course runs across 8 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.

  • Introduction to No-Code AI Automation — Understand the core concepts of triggers, actions, and API-less integrations. Map out a manual workflow to prepare it for automation in Zapier and Make.
  • Building Your First Zapier AI Workflow — Set up a Zapier account, connect a trigger app (like Gmail or Typeform), and configure a basic action step that sends data to an AI model.
  • Configuring AI Prompts and Steps in Zapier — Learn how to write effective system prompts within Zapier's OpenAI/AI steps, map dynamic variables from previous steps, and test the output.
  • Introduction to Make (Integromat) Visual Builder — Navigate the Make visual canvas, understand scenarios, modules, and data mapping, and set up a basic data routing workflow.
  • Integrating AI Modules in Make — Connect OpenAI or Anthropic modules in Make. Learn how to parse JSON payloads and structure the AI's response for downstream apps.
  • Multi-App Workflows and Data Routers — Create complex paths using Zapier Paths or Make Routers to send AI-generated content to different destinations (e.g., Slack, Notion, or Google Sheets) based on conditions.
  • Error Handling and Edge Cases in AI Runs — Set up error-catcher steps and filters to handle empty payloads, API timeouts, or unexpected AI formatting errors without breaking the live workflow.
  • Testing, Deploying, and Monitoring Your Automations — Perform end-to-end testing of your active workflows, review history logs to troubleshoot errors, and optimize task/operation usage to manage costs.

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. This course maps to Critical Thinking, Data Analysis, Generative AI Concepts, AI Ethics, Content Strategy.

  • Critical Thinking
  • Data Analysis
  • Generative AI Concepts
  • AI Ethics
  • Content Strategy

Who it is for

Ops, marketing, all teams. The material is pitched at intermediate level, and takes roughly 120 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 →
  • AI Automation & Integration — Learners connect AI into workflows and systems using no-code tools, APIs, and MCP. The course covers no-code automation, APIs and webhooks, MCP and connectors, and workflow design. Participants finish able to wire AI into the systems they already use.
  • 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.
  • AI Automation Assessment — AI Automation Assessment: designing and running a reliable workflow.
  • AI for Operations & IT — Automate processes and support with AI
  • AI Automation Specialist — Connect AI into real workflows and systems

Related

Frequently asked questions

How long does this course take?

It runs roughly 120 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-101.