Open education dataset · Version 1.0.0

AI Literacy Curriculum & Competency Framework

A reusable public framework connecting 30 competencies to five outcome-based courses, practice tasks, and applied capstones. Published August 27, 2026 under CC BY 4.0.

Download JSON Explore the courses
Competencies
30
Courses
5
Modules
20
Estimated hours
29

The framework

Competency map

Each tile shows which courses teach the competency; the bar shows how many modules map to it.

  • AI Foundations
  • Responsible AI User
  • AI at Work
  • AI Policy & Society
  • Building with AI Systems
  1. 01
    AI concepts and boundaries
    ai-concepts
  2. 02
    Data, training, and generalization
    data-training
  3. 03
    Models, inference, and limitations
    model-inference
  4. 04
    Evaluation and benchmark literacy
    evaluation
  5. 05
    Uncertainty and confidence calibration
    uncertainty
  6. 06
    Source and claim verification
    source-verification
  7. 07
    Prompt and context design
    prompt-design
  8. 08
    AI-assisted workflow design
    workflow-design
  9. 09
    Output review and error detection
    output-review
  10. 10
    Tool selection and comparison
    tool-selection
  11. 11
    Automation boundaries and safeguards
    automation-safety
  12. 12
    Privacy and data handling
    privacy
  13. 13
    Bias and fairness
    bias-fairness
  14. 14
    Copyright and content provenance
    copyright
  15. 15
    AI security and misuse risk
    security
  16. 16
    Governance and accountability
    governance
  17. 17
    AI policy and regulation
    policy
  18. 18
    Workforce and job impacts
    workforce
  19. 19
    Language-model mechanics
    llm-mechanics
  20. 20
    Retrieval-augmented generation
    rag
  21. 21
    Agents, tools, and long-running tasks
    agents
  22. 22
    Multimodal AI systems
    multimodal
  23. 23
    Model cost and operational tradeoffs
    model-cost
  24. 24
    Experiment and pilot design
    experiment-design
  25. 25
    Success metrics and monitoring
    metrics
  26. 26
    AI incident response
    incident-response
  27. 27
    Stakeholder communication
    stakeholder-communication
  28. 28
    Public-interest impact analysis
    public-interest
  29. 29
    AI career readiness
    career-readiness
  30. 30
    Continuous AI learning
    continuous-learning

Architecture

Course architecture

Beginner4 estimated hours

AI Foundations

Understand what AI is, how systems learn, where they fail, and how to judge claims without hype.

4 modules · 4 estimated hours · Capstone: AI claim fact check

Beginner5 estimated hours

Responsible AI User

Use AI productively while protecting privacy, checking outputs, and preserving human accountability.

4 modules · 5 estimated hours · Capstone: Human-in-the-loop workflow

Intermediate6 estimated hours

AI at Work

Evaluate workplace use cases, run safe pilots, measure value, and communicate changes responsibly.

4 modules · 6 estimated hours · Capstone: AI pilot proposal

Intermediate6 estimated hours

AI Policy & Society

Analyze AI systems through rights, equity, governance, safety, and public-interest outcomes.

4 modules · 6 estimated hours · Capstone: Public-interest AI briefing

Intermediate8 estimated hours

Building with AI Systems

Understand language models, retrieval, agents, evaluation, cost, and deployment safeguards through practical system design.

4 modules · 8 estimated hours · Capstone: AI system design review

Method and limits

Method and limits

The framework is designed around observable objectives, deliberate practice, and portfolio evidence. This release does not claim proven completion or retention outcomes; those benchmarks require enough consented learner data over time. Version changes will be dated and the stable JSON endpoint will remain available for reuse and citation.