Responsible AI Curriculum
Build the skills for a responsible AI society.
Structured learning roadmaps that take students, professionals, engineers and leaders from first principles to confident practice — grounded in ISO/IEC 42001, the EU AI Act, NIST AI RMF and India's AI governance frameworks.
Responsible AI isn't only a compliance task. It's a shared capability a society has to build — across classrooms, boardrooms, codebases and policy desks. This curriculum is open guidance to help anyone start, wherever they are today.
Step 1
Choose your path
Your roadmap
Students & Early Career
New to AI governance and building a foundation (and a career).
Stage 1 · Foundations of AI & Society
2–3 weeksUnderstand what AI is and why responsible AI matters.
How AI actually works (no code)
3–4 hrs- What machine learning and generative AI are
- Training data, models, predictions
- Where AI shows up in daily life
By the end you can explain in plain language how an AI system makes a decision.
Why responsible AI matters
3–4 hrs- Real-world AI harms: bias, privacy, deepfakes, fraud
- The cost of getting it wrong
- Society-level impact
By the end you can describe several real AI harms and why governance exists.
The principles of responsible AI
2–3 hrs- Fairness, transparency, accountability
- Privacy, safety, human oversight
- Explainability and inclusivity
By the end you can name and define the core responsible-AI principles.
Stage 2 · The Rulebook: Frameworks & Standards
3–4 weeksGet oriented in the major AI governance frameworks.
Global frameworks
4–5 hrs- ISO/IEC 42001 (AI management systems)
- NIST AI RMF: Govern, Map, Measure, Manage
- EU AI Act risk pyramid
By the end you can explain what each major framework is for.
India's approach
4–5 hrs- India AI Governance Guidelines & the seven sutras
- DPDP Act basics
- RBI FREE-AI (intro)
By the end you can summarise how India governs AI through existing laws + sectoral regulators.
Stage 3 · Seeing Governance in Action
3–4 weeksUnderstand the core artefacts and how they work.
Inventories & impact assessments
3–4 hrs- What an AI inventory is
- DPIA + AI impact assessment
- Risk tiering
By the end you can read and understand a real AI impact assessment.
Fairness, explainability & oversight
3–4 hrs- How bias enters a model
- What explainability means
- Human-in-the-loop
By the end you can spot fairness and oversight gaps in an AI use case.
Stage 4 · Build Your Profile
2–3 weeksTurn knowledge into a starter portfolio and a path.
Practice with real templates
4–6 hrs- Complete a mock inventory + impact assessment
- Use a governance policy template
By the end you can produce sample governance artefacts for your portfolio.
Assess & plan your career
3–4 hrs- Take the AI Governance Assessment
- Career paths: analyst, privacy, risk, policy
- Mini-project: govern a public AI product
By the end you can have a portfolio piece and a clear next step.
Join the movement
Want to be responsible — and help build a responsible AI society?
AramGRC is building a global community of students, engineers, leaders and policymakers committed to safe, fair and accountable AI. Learn together, share practice, and raise the bar — wherever you are.
Coming soon