LearnAI by SAI4RAI
Complete beginner path

AI Builder Foundations

A complete beginner path from curiosity to one small AI project with documented learning evidence.

6-8 hours total beginner
Path map

Ten steps from curiosity to evidence.

  1. Start Here.
    Read the first learner walkthrough.
  2. Mindset.
    Write your first AI Builder note.
  3. Find a problem.
    Create one problem brief.
  4. Try a prototype.
    Test one tiny safe workflow.
  5. Document.
    Turn the test into a project story.
  6. Sprint days 1-3.
    Build rhythm with short daily practice.
  7. Choose a project.
    Pick one narrow workflow from your notes.
  8. Create artifact.
    Save one portfolio-ready note.
  9. Reflect.
    Write one private or public learning reflection.
  10. Choose next path.
    Continue the sprint, repeat the path, or explore Legal AI.

Expected learner outputs

One problem brief, one tiny prototype note, one reviewed output, one project story, and one reflection note.

Downloadable Worksheets & Templates

Use the printable Markdown worksheets to observe workflows, log experiments, iterate prompts, check safety, reflect, and shape your portfolio artifact.

Open worksheets

Responsible AI checkpoints

Use public, fictional, or low-risk data. Keep human review visible. Do not upload sensitive information while practicing.

Completion criteria

You are done when you can explain the problem, what you tried, what AI helped with, what humans reviewed, and what you will improve next.

Who This Path Is For

This path is for complete beginners who want to move from curiosity to a small finished AI project without feeling rushed or overwhelmed.

It is useful for students, MS aspirants, beginner professionals, nonprofit/community learners, mentors, and anyone who wants evidence of practical learning.

What You Will Be Able To Do By The End

By the end, you should be able to:

  • notice one real workflow problem
  • describe a safe AI use case
  • test one tiny AI-assisted workflow
  • document what you tried
  • save one portfolio artifact
  • write one reflection
  • explain one responsible AI boundary

Time Commitment

Plan for 6-8 hours total. You can complete it across one weekend, one week, or a slower two-week rhythm.

Prerequisites

No coding or technical background is required.

You need:

  • a notebook or document
  • access to an AI tool you are allowed to use
  • willingness to practice with fictional, public, or low-risk information
  • patience to build one small thing carefully

Learning Outcomes

You will learn how to:

  • think like an AI builder
  • find real problems before choosing tools
  • test tiny prototypes safely
  • document prompts, outputs, and review notes
  • turn practice into portfolio evidence
  • reflect on learning and next steps

Step-by-Step Path Map

  1. Start Here: read the first learner walkthrough.
  2. AI Builder Mindset: write your first AI Builder note.
  3. Find Real Problems: create one problem brief.
  4. Try Tiny AI Prototypes: test one safe, narrow workflow.
  5. Document Your Work: turn the test into a project story.
  6. Complete 7-Day Sprint Days 1-3: build rhythm through small daily practice.
  7. Choose one tiny project: select the safest project idea from your notes.
  8. Create one portfolio artifact: save a project story or prototype note.
  9. Write one public or private reflection: name what worked, what needed review, and what comes next.
  10. Decide your next path: continue the sprint, explore Legal AI, or repeat Foundations with a new problem.

Required Modules

Required Labs

Required Reflection Artifacts

Create these short notes:

  • “Why I want to learn AI responsibly”
  • “One real workflow problem I noticed”
  • “What AI helped with and what a human reviewed”
  • “What I would improve in version two”

Portfolio Outputs

By the end, save:

  • one problem brief
  • one tiny prototype note
  • one documented prompt and reviewed output
  • one project story
  • one reflection note

Use the Downloadable Worksheets & Templates page for printable Markdown templates that match these outputs.

Responsible AI Checkpoints

Stop and check before each activity:

  • Am I using public, fictional, or low-risk data?
  • Am I avoiding private, sensitive, legal, medical, financial, educational, or personal data?
  • Can a human review the output?
  • Am I clear that this is a learning prototype?
  • Have I avoided overstating what AI can do?

Suggested External Resources

Use external resources as learning inputs, not as a replacement for practice.

Suggested sources:

  • OpenAI Academy beginner sessions
  • Microsoft Learn AI fundamentals
  • Google AI learning resources
  • one practical YouTube tutorial on prompting
  • one book chapter or article on responsible AI

After each external resource, write three takeaways and apply one takeaway to your tiny project.

Final Mini-Project

Create one small AI-assisted workflow using safe sample information.

Your project should:

  • solve one narrow workflow problem
  • use fictional, public, or low-risk data
  • include the prompt you tried
  • include the AI output
  • include human review notes
  • include a responsible AI warning
  • include one next improvement

Completion Checklist

  • I completed the Start Here walkthrough.
  • I wrote an AI Builder Mindset note.
  • I created one problem brief.
  • I tested one tiny AI prototype safely.
  • I documented prompts, outputs, and human review.
  • I completed Sprint Days 1-3.
  • I saved one portfolio artifact.
  • I wrote one reflection note.
  • I named one responsible AI boundary.
  • I chose my next learning path.