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