Linkedin Learning – Knowledge Graph Data Engineering For Generative AI Use Cases

This advanced course bridges the gap between traditional data engineering and modern AI applications through knowledge graphs. Designed for data scientists and engineers, instructor Ashleigh Faith provides an overview of a practical framework for implementing neurosymbolic AI solutions. Learn how to assess data requirements, build robust knowledge graphs, implement efficient ETL processes, and handle complex entity resolution challenges. Along the way, Ashleigh covers real-world applications, common pitfalls, and best practices for creating maintainable, scalable knowledge graph solutions that can integrate with AI systems.

RAPIDGATOR:
https://rapidgator.net/file/5ea8e0407ae3dfc3eaea433bc541e81e/Linkedin.Learning.Knowledge.Graph.Data.Engineering.For.Generative.AI.Use.Cases.BOOKWARE-SCHOLASTiC.rar.html

TURBOBIT:
https://trbt.cc/m2m39jygu00r/Linkedin.Learning.Knowledge.Graph.Data.Engineering.For.Generative.AI.Use.Cases.BOOKWARE-SCHOLASTiC.rar.html