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CodeSignal

Knowledge Graphs for Connected Context

via CodeSignal

Overview

You'll learn to reason in nodes, edges, and relationships, and to judge when connected context better supports certain relationship-centered or variable-depth questions than tables and hierarchies do. You'll practice separating observed relationships from inferred cause and translating graph evidence into decision-ready advice without writing code or producing technical data designs.

Syllabus

  • Unit 1: Core Graph Concepts
    • When Rows Win and When Connections Win
    • Mapping the Language of Graphs
    • Explaining Connected Context to a Skeptic
  • Unit 2: Entity and Relationship Meaning
    • Entity Resolution Beyond Duplicate Records
    • Decoding Data Identity Concepts
    • Reading Identity Before Approving Merges
  • Unit 3: Evaluating Graph Fit
    • Identifying Use Cases and Failure Modes
    • Matching Connected Use Cases to Questions
    • Bounding a Sponsor's Graph Ambition
  • Unit 4: Interpreting Connected Evidence
    • Reading Co-Occurrence Without Naming a Culprit
    • Observed, Inferred, or Just Structural?
    • Separating Observed Links From Inferred Blame

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