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Mastering the Semantic Web: From RDF to Knowledge Graphs
Bestseller
Highest Rated
Rating: 4.8 out of 5(60 ratings)
262 students

Mastering the Semantic Web: From RDF to Knowledge Graphs

Learn core Semantic Web technologies like RDF, RDFS, OWL, SPARQL and SHACL to build extensive ontologies.
Bestseller
Highest Rated
Created byAl-Hakam Hamdan
Last updated 10/2025
English

What you'll learn

  • Master the core of the Semantic Web Stack including RDF, RDFS, OWL, SPARQL & SHACL.
  • Get a deep understanding of how ontologies & knowledge graphs work.
  • Develop fully functional apps in python fueled by knowledge graphs.
  • Apply best practices to develop your own OWL ontology in Protege
  • Host and manage your knowledge graph in the professional triplestore GraphDB

Course content

7 sections • 88 lectures • 10h 38m total length

  • What you're going to get from this course1:39
  • Glossary for this course0:20
  • Why do we need the Semantic Web?7:18
  • Linked Data6:59
  • The Semantic Web Stack1:55
  • Recap of URIs1:07

Requirements

  • Basic knowledge of programming and building simple applications (preferably Python)
  • macOS, Linux or Windows machine with access to the internet
  • No paid software required
  • Positive attitude and willingness to learn!

Description

Welcome to the ultimate course on mastering the Semantic Web Stack – including RDF, SPARQL, RDFS, OWL, SHACL, and more – with hands-on projects using Python, RDFlib, OWLReady2, and Protégé.

If you’ve ever wanted to dive into the world of Linked Data, Ontologies, or Knowledge Graphs but didn’t know where to start this course is your complete guide.

You’ll learn how to model, query, validate, and reason with structured data using powerful Semantic Web technologies. This Tech is used by companies like Google, Microsoft, IBM and in Wikipedia. With these technologies you are capable of creating knowledge graphs that work as symbolic AI and can be part of other AI systems.

Whether you're a developer, data scientist, researcher, or just curious about the future of AI: these skills will take your technical profile to the next level.

This course is packed with state-of-the-art knowledge and hands-on examples, including:

  • RDF for structuring data in graphs

  • SPARQL for querying knowledge graphs

  • RDFS and OWL for building expressive ontologies that reason automatically for implicit information

  • SHACL for validating RDF graphs and providing data consistency

  • Development of Python-based apps that are fueled by ontology frameworks like RDFlib or OWLReady2

  • Ontology modeling in Protégé

  • Managing your knowledge graphs in the web on triplestores like GraphDB

You’ll also work on practical projects applying best practices in the Ontology Lifecycle - from requirements gathering to publication.

This course will give you a solid foundation to become a professional Ontologist / Knowledge Engineer.

Who this course is for:

  • Intermediate developers interested in Semantic Web technologies and knowledge engineering
  • AI researchers who need to model, query, and reason over structured knowledge
  • Data scientists looking to enhance data integration with graph-based approaches beyond traditional relational databases

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