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Agentic Knowledge Graphs

AI agents often generate answers without true understanding or explainability. This course will teach you how to design agent-driven knowledge graphs that enable structured reasoning, contextual understanding, and explainable decision-making.

Intermediate
1h 16m

Created by Gihad Sohsah

Last Updated Feb 09, 2026

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  • Course

Agentic Knowledge Graphs

AI agents often generate answers without true understanding or explainability. This course will teach you how to design agent-driven knowledge graphs that enable structured reasoning, contextual understanding, and explainable decision-making.

Intermediate
1h 16m

Created by Gihad Sohsah

Last Updated Feb 09, 2026

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What you'll learn

Many AI agents can retrieve information but still fail to reason effectively or explain how they reach their conclusions. In this course, Agentic Knowledge Graphs, you’ll learn to design and build agent-driven knowledge graphs that enhance reasoning and explainability in AI systems. First, you’ll explore the foundations of knowledge graphs, including entities, relationships, and schemas that support agentic reasoning. Next, you’ll discover how to construct and integrate knowledge graphs using agents that extract and connect data from structured and unstructured sources. Finally, you’ll learn how to apply knowledge graphs in real-world agentic workflows using tools like Neo4j and LangChain to enable contextual querying and explainable decision-making. When you’re finished with this course, you’ll have the skills and knowledge of agentic knowledge graphs needed to build intelligent, structured, and transparent AI agents that provide reasoning.

Agentic Knowledge Graphs
Intermediate
1h 16m
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About the author
Gihad Sohsah - Pluralsight course - Agentic Knowledge Graphs
Gihad Sohsah
1 courses 0.0 author rating 0 ratings

Gihad Sohsah is an AI engineer and entrepreneur with 13+ years of experience building deployable machine learning systems, creative AI solutions, and educational content.

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