Enterprise Ontology Engineering With Protégé, Rdf, Owl,

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Enterprise Ontology Engineering With Protégé, Rdf, Owl,
Published 7/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 4h 15m | Size: 2.2 GB
Design, Build, Deploy, and Query Enterprise Knowledge Graphs using Semantic Web Technologies with Hands-on Projects and
What you'll learn
Build enterprise-grade healthcare ontologies using Protégé, RDF, RDFS, OWL, Apache Jena Fuseki, and SPARQL.
Design, model, query, and validate semantic knowledge graphs using industry-standard Semantic Web technologies.
Create a complete healthcare knowledge graph project from ontology design to deployment using real-world best practices.
Gain the foundation required to build production-ready Knowledge Graph and AI applications using Neo4j, SHACL, and Python in Part 2.
Requirements
No prior knowledge of Semantic Web or Knowledge Graphs is required.
A willingness to learn ontology engineering and Semantic Web technologies.
A computer with at least 8 GB RAM (16 GB recommended) to install Protégé and Apache Jena Fuseki.
Basic Programming knowledge in Python is required.
Description
Knowledge Graphs and Ontologies have become foundational technologies for Artificial Intelligence, Enterprise Data Integration, Semantic Search, Digital Twins, Healthcare Informatics, Finance, Manufacturing, and many other domains. Organizations worldwide are adopting Semantic Web technologies to build intelligent, connected, and reusable knowledge systems.
This course provides a comprehensive, hands-on introduction to Enterprise Ontology Engineering using industry-standard Semantic Web technologies. Whether you are a software engineer, data engineer, AI practitioner, researcher, or student, this course will equip you with the practical skills required to design, develop, deploy, and query enterprise knowledge graphs.
Starting from the fundamentals of Knowledge Representation, you will progressively learn RDF, RDFS, OWL, Protégé, Apache Jena Fuseki, SPARQL, SKOS, and Ontology Design Patterns. Every concept is demonstrated through practical examples, culminating in the development of a complete Healthcare Knowledge Graph.
Unlike theory-focused courses, this program emphasizes practical implementation. You will build ontologies from scratch, create semantic relationships, populate knowledge graphs with real-world data, deploy them in Apache Jena Fuseki, and retrieve information using SPARQL.
The course also includes multiple hands-on laboratory exercises and a capstone project where you will independently design and develop an enterprise knowledge graph for a business domain of your choice.
By the end of this course, you will have the confidence and practical experience to design semantic solutions for healthcare, finance, retail, manufacturing, education, government, logistics, and many other industries.
Whether you are beginning your Semantic Web journey or looking to strengthen your enterprise ontology engineering skills, this course provides the knowledge, practical experience, and best practices needed to build production-ready knowledge graphs.
Who this course is for
Enterprise Architects designing semantic data platforms and knowledge management systems.
AI, Machine Learning, and Generative AI Engineers who want to integrate structured knowledge into intelligent applications.
Data Engineers and Data Architects working with enterprise data integration.
Researchers and students in Computer Science, Artificial Intelligence, Healthcare Informatics, and Data Science.
Software Engineers interested in Knowledge Graphs and Semantic Web technologies.
Anyone interested in learning RDF, OWL, Protégé, Apache Jena Fuseki, and SPARQL through a real-world healthcare project.

Code:

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