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AIN-101 AI-Native: Working and Building with Generative AI

AIN-101 AI-Native: Working and Building with Generative AI

An 'AI for Everyone' foundation course: move from simply being AI-aware to working AI-native, through the right mindset, structured prompting, and one AI workflow built from your own job.

Join this Course
Responsible Hinata Yuji
Last Update 10/08/2026
Completion Time 1 hour 35 minutes
Members 1
  • From AI-Aware to AI-Native
    • What Does AI-Native Mean?
      New
    • How Generative AI Works: 'The AI Said So' Is Not Proof
      New
    • Eight AI-Native Mindsets
      New
  • Getting to Know Claude's Services
    • Assistants That Answer vs Agents That Act
      New
    • Which to Use When: Projects, Styles, and Moving from ChatGPT
      New
  • Outcome Thinking & Prompting
    • Outcome Thinking and the R-T-C-F Pattern
      New
    • Prompting Practice: From Weak Prompts to Reliable Ones
      New
  • Building Your AI Workflow
    • Find Your Use Case
      New
    • MCP, the Adoption Ladder, and Your Workflow Plan
      New
    • AIN-101 Final Quiz
      New 10 xp

From AI-Aware to AI-Native

Many people are already 'AI-aware': they ask a chatbot something now and then, and stop there. AIN-101 helps you go further, making AI part of your everyday way of working and building your own workflows from real tasks. The end goal is simple: work that is faster, higher in quality, and more consistent.

Who is this course for?

  • Anyone, in non-technical or technical roles. No coding skills required.
  • Office workers, professionals, students, and business owners who want to use AI purposefully and responsibly.
  • Anyone with repetitive tasks who wants that time back for more valuable work.

What you will learn

  1. Explain what generative AI is, how it works in simple terms, its limits, and when to use an assistant versus an agent.
  2. Write effective prompts using the R-T-C-F pattern and outcome-first thinking.
  3. Map your own activities and design at least one AI use case or workflow.
  4. Evaluate and verify AI output responsibly, including the preview-then-confirm principle.

How to learn

This course is self-paced. Each lesson contains a short concept and exercises you can try right away with the AI assistant of your choice; the service used as the example is Claude. Bring one repetitive task from your own work as practice material, then finish with the final quiz.

AI for everyone: the key is thinking skills, not coding.