OneRange

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.

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 AI Workflows & No-Code Automation — Understand the landscape of AI integration, mapping manual tasks to automated triggers, and setting up your first no-code automation flow.
  • Connecting Systems with APIs and Webhooks — Learn the fundamentals of REST APIs, authenticating requests, and configuring webhooks to send real-time data payloads between applications.
  • Hands-on No-Code Integration — Build a live multi-step automation using a no-code platform (e.g., Make or Zapier) to parse incoming data and pass it to an AI model.
  • Demystifying Model Context Protocol (MCP) — Explore the architecture of Model Context Protocol (MCP), how it standardizes client-server connections, and its role in secure data sharing.
  • Building and Configuring MCP Connectors — Develop and deploy custom MCP connectors to expose local databases and enterprise systems directly to LLM-powered applications.
  • Strategic Workflow Design and Error Handling — Design resilient AI workflows incorporating conditional logic, retry mechanisms, human-in-the-loop validation, and rate-limit handling.
  • Securing AI Integrations and Data Privacy — Best practices for managing API keys, securing webhook endpoints, anonymizing PII, and maintaining compliance within automated pipelines.
  • Capston Lab: Deploying an End-to-End AI Agent — Synthesize your skills by building, testing, and debugging a fully integrated AI workflow that utilizes webhooks, APIs, and custom MCP connectors.

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 Working with AI Tools, Webhooks, Workflow Design & Automation, Workflow Automation, API Integration.

  • Working with AI Tools
  • Webhooks
  • Workflow Design & Automation
  • Workflow Automation
  • API Integration

Who it is for

Ops, builders, technical users. The material is pitched at intermediate 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 Category: 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, code lab 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 →
  • 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.
  • 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 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 CAT-AUT.