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AI Vibe Coding for Non-Developers
Course 4725
1 DAY COURSE

Course Outline

This one-day instructor-led course teaches non-technical business professionals how to use modern AI tools to turn a business idea into a working web application, without writing code.

Participants learn how to express business ideas as clear instructions for an AI tool, guide the tool to build a simple web app, verify that the results match their intent, and improve the app through step-by-step refinement. Rather than learning programming syntax, the course focuses on clear thinking, iteration, validation, and explanation.

Throughout the day, learners build a simple web application that asks a few questions and provides clear recommendations with an explanation. By the end of the course, each participant has built, run, and demonstrated a working web app using an AI tool, and understands when and how to use this approach responsibly in a business environment.

AI Vibe Coding for Non-Developers Benefits

  • Course Benefits

    • Use AI tools to turn business ideas into simple, working applications
    • Take an unclear idea and turn it into something they can run and demonstrate in one day
    • Build and use a basic web-based decision tool without writing code
    • Create early versions of solutions without waiting on technical teams
    • Clearly explain what an AI-built tool does, why it gives its results, and where its limits are

    Prerequisites

    • General business experience
    • Ability to describe problems, rules, or decisions in plain language
    • No technical or coding prerequisites

AI Vibe Coding for Non-Developers Training Outline

Learning Objectives

Module 1: Introduction to AI Vibe Coding

  • What AI Vibe Coding means for non-developers
  • How generative AI tools function as development assistants
  • Differences between traditional development and AI-assisted development
  • Human-in-the-loop responsibility
  • Overview of the application to be built

Module 2: Framing the Decision Problem

  • Why clarity drives AI performance
  • Defining a decision vs. defining a solution
  • Identifying decision-maker, outcomes, and constraints
  • Establishing measurable success criteria
  • Lab 1: Transform a vague business idea into a clear, scoped decision problem.

Module 3: App Concept and User Flow

  • What an app concept means in business terms
  • Inputs vs. outputs
  • Designing for clarity and simplicity
  • Avoiding early overengineering
  • Lab 2: Design the App Structure - Translate the decision problem into an app concept.

Module 4: Business Rules and Logic

  • What business logic means
  • Converting policies into conditions
  • Making thresholds explicit
  • Ensuring explainability
  • Lab 3: Translate Rules into Logic - Convert business rules into structured decision logic using AI.

Module 5: Building the Web App

  • What AI-generated applications look like
  • How to request a browser-based app
  • Running AI-generated output safely
  • Understanding draft vs. production software
  • Lab 4: Generate and Run the App - Build a runnable web application.

Module 6: Validation and Refinement

  • AI limitations
  • Edge case testing
  • Improving clarity and explanations
  • Human accountability
  • Lab 5: Strengthen Reliability - Test, refine, and improve trust in the application.

Module 7: Final Demonstration

  • Demonstrating business value
  • Explaining decisions clearly
  • Communicating limits and risks
  • LAB 6: Demonstrate and Explain the App - Present the app as if to a stakeholder.

Module 8: Governance, Risk, and Responsible Use

  • Human accountability
  • Risks of over-reliance
  • When to involve technical teams
  • Appropriate enterprise boundaries
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Private Team Training

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