Knowledge Graphs
Knowledge Graphs
Even though it affects our lives every single day, most of us have no idea what a knowledge graph is. Asking Alexa about the weather tomorrow or searching for the latest news on climate change via Google, knowledge graphs constitute the backbone of today’s state-of-the-art information systems. From improving search results over question answering and recommender systems up to explainable AI systems, the applications of knowledge graphs are manyfold.
In this course you will learn what is necessary to design, implement, and use knowledge graphs. The focus of this course will be on basic semantic technologies including the principles of knowledge representation and symbolic AI. This includes information encoding via RDF triples, knowledge representation via ontologies with OWL, efficiently querying knowledge graphs via SPARQL, latent representation of knowledge in vector space, as well as knowledge graph applications in innovative information systems, as e.g., semantic and exploratory search.
Requirements for this Course:
- Basic understanding of web technologies, such as URL and HTTP
- Basic understanding of mathematics, in particular statistics and probability theory
- Basic knowledge of database technology, such as relational databases and SQL query language
Intended Audience:
- Students of computer science or related subjects at bachelor or master level
- Researchers and scientists interested in the web, knowledge representation, semantic web technologies, ontology engineering, machine learning, artificial intelligence
- Young professionals, in particular knowledge engineers, data & web scientists
- Students, researchers and professionals in the field of digital humanities and cultural heritage (e.g. working in archives, libraries, and museums)
Duration: Not defined
Level: Expert
Certification: Yes
Cost: Free
Language: English
Type: Self-Paced
Please note: these courses are provided by external sources, links are not actively managed or regularly updated, content might be moved or unavailable.