Course Overview
Explore ontologies for AI engineers, focusing on knowledge graphs, SHACL, and grounded agents. Learn how to implement constraints, validate AI models, and ensure reliable results in AI applications. This course covers the role of constraints in preventing inconsistencies, the impact of open and closed world assumptions, and how to use SHACL to define and enforce schemas for auditing AI outputs.
Gain practical experience with ontology creation and shape definitions to improve decision-making and prevent semantic errors in AI systems. The course is designed for technical AI engineers, developers, and professionals involved in AI model development and validation.
Course introduction 5m 21s
Where the constraint lives 2m 9s
The shape of a model 3m 1s
Four sincere numbers 3m 56s
The write path 4m 57s
Terminological Box (TBox) and Assertional Box (ABox) 3m 48s
Welcome to Shapes Constraint Language (SHACL) 2m 53s
Shape of a plate 1m 50s
Closed shape rejects undeclared 3m 6s
The missing auditor 4m 37s
Targets and coverage 3m 24s
Subsumption without a reasoner 4m 26s
A fact nobody wrote 2m 1s
Where this goes 4m
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