Responsible AI & Governance Certification

From AI Observer to AI Governance Lead

A practitioner-grade certification for the professionals who must navigate the 'black box' of AI and ensure compliant, ethical adoption. Anchored to a 'Bring Your Own Project' (BYOP) system you carry across all six modules, you'll produce a deployable governance portfolio — Risk Register, EU AI Act tier classification, NIST AI RMF mapping, Model Card, RACI matrix, and a 90-Day Implementation Roadmap.

Curriculum

Module 01

Welcome to Responsible AI & Governance Certification

Orient to the certification, select your BYOP system, and set personal learning goals.

1 lessons

1
Course Overview & BYOP
- Navigating the 'black box' of AI
- Bring Your Own Project (BYOP) approach
- Trust-by-Design as competitive advantage
- Building your governance portfolio

Module lab · ~45 min

Building Your Governance Baseline: AI Inventory & BYOP Selection

Module 02

The AI Governance Landscape

EU AI Act risk tiers, the NIST AI RMF, and the three-step risk triage.

1 lessons

1
EU AI Act vs NIST AI RMF
- Extraterritorial reach of the EU AI Act
- Four risk tiers: Unacceptable, High, Limited, Minimal
- NIST: Govern, Map, Measure, Manage
- Three-step triage: domain, autonomy, rights impact

Module lab · ~45 min

FinStream AI Risk Triage and Governance Strategy

Module 03

Ethics by Design

Translating ethical values into technical requirements, HITL workflows, and GenAI guardrails.

1 lessons

1
From Post-Hoc Panic to Ethics by Design
- Translating values into KPIs
- Confidence Thresholding & HITL
- Dual-Gated input/output filters
- Red Teaming and Red Button protocols

Module lab · ~60 min

Designing Ethical Guardrails for FinStream's AI Loan Assistant

Module 04

Risk Assessment & Data Governance

AI failure modes, Risk Priority Numbers, and the L-O-C data governance framework.

1 lessons

1
Risk Registers & L-O-C
- Brittleness and silent AI failure
- RPN = Likelihood × Impact
- Lineage, Ownership, Consent (L-O-C)
- HITL, Data Minimization, Consent Re-validation

Module lab · ~60 min

Building Your First AI Risk & Data Governance Registry

Module 05

Bias Auditing & Transparency

The 4/5ths Rule, proxy variables, explainability layers, and Model Cards.

1 lessons

1
Quantitative Bias & Model Cards
- The 4/5ths Rule for Disparate Impact
- Proxy variables and fairness gerrymandering
- Local explainability (LIME / SHAP)
- Margaret Mitchell Model Card framework

Module lab · ~75 min

Conducting a Bias Audit and Transparency Report for Credit Limit Increases

Module 06

Building a Governance Framework

AI RACI with the 'One A' rule, ADKAR change management, and a 90-day roadmap.

1 lessons

1
RACI, ADKAR & 90-Day Roadmap
- The 'One A' rule for accountability
- ADKAR: Awareness → Reinforcement
- Discovery → Integration → Operationalized Oversight
- Bias-aware Definition of Done

Module lab · ~75 min

Implementing the AI Governance Blueprint for ApexCredit

Module 07

Capstone: 90-Day AI Governance Roadmap

Produce a complete governance package for your BYOP (or the MidCity Health case).

1 lessons

1
Capstone Deliverables
- AI Risk Register (8+ risks, RPN-sorted)
- EU AI Act tier + NIST mapping memo
- Model Card with disaggregated evaluation
- RACI matrix, Why Statement, 90-Day Roadmap

Module lab · ~360 min

Your Organization's 90-Day AI Governance Roadmap