Architecting Reasoning for Enterprise AI

Master how to bridge the gap between LLM reasoning limitations and structured knowledge by integrating semantic data models and knowledge graphs into robust enterprise AI architectures. * **Map knowledge graphs** to LLM reasoning patterns * **Identify abduction gaps** in automated data inference * **Design semantic schemas** that reduce model hallucinations * **Integrate structured metadata** for reliable AI reasoning

3 sections ยท 7 lessons

Course outline

Inference Modes

  1. Induction Limits
  2. Deductive Verification
  3. Abductive Leaps

Axiom Modeling

  1. Axiom Formulation
  2. Constraint Validation

Grounded Intelligence

  1. Symbol Grounding
  2. Interactive Simulation

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