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Artificial Intelligence Essentials

AI Governance - Module3


Content
  • Level 1: Module 1
  • AI Governance Fundamentals
  • 1.1 AI Governance Fundamentals
  • 1.2 AI system types: predictive ML vs rules vs GenAI; where the risks differ
  • 1.3. Value & risk lens: why governance exists
  • 1.4. Core governance components
  • 1.5. The AI lifecycle
  • 1.6 Accountability basics
  • 1.7 Case Studies
  • 1.8. Minimum viable governance
  • Module 1 Assessment
  • AI Literacy for Organisations
  • 2 AI Literacy for Organisations
  • 2.1 AI in plain English:
  • 2.2 Data handling rules
  • 2.3 Safe usage patterns
  • 2.4 Acceptable Usage Policy
  • 2.5 Human Oversight
  • 2.6 Bias and fairness basics
  • 2.7 IP and confidentiality
  • 2.8 Incident & escalation
  • Video unit
  • Video unit
  • AI Usage Pledge
  • 2.7 IP and confidentiality: prompts, outputs, copyright, trade secrets
  • 2.8 Incident & escalation: red flags, reporting routes, evidence (clone)
  • Level 1 Module 2 Assessment
  • Responsible GenAI Use in the Enterprise
  • 3.1 GenAI Fundamentals: tokens, context windows, hallucinations, grounding
  • 3.2 Prompting for business task framing, constraints, structured outputs
  • 3.3 Quality controls: verification loops, cross-checking, confidence signalling
  • 3.4 Data protection in GenAI: redaction patterns; secure alternatives
  • 3.5 HITL design: approval steps, review checklists, accountable owner
  • 3.6 Operational controls: logging, access, retention, model/tool selection
  • 3.7 Use-case playbooks: summary, drafting, analysis, customer comms, coding
  • 3.8 Failure modes: prompt injection basics, output harms, rollbacks
  • Video ​unit​
  • Video ​unit​ (clone)
  • Video unit
  • Checking Heygen videos
  • 2.5 Human oversight: When you must Review, Approve, or Escalate?
  • 2.6 Bias and fairness basics
  • 3.2 Prompting for business task framing, constraints, structured outputs
Completion rules
  • All units must be completed
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