Until now, it has been fairly difficult for learners to readily access curated materials on the topic of knowledge graph, largely due to the fairly patchy and technical landscape that we need to navigate when trying to understand the subject area. This course is a game changer, bringing to life the starting point for your journey to becoming an expert in knowledge graph technology, semantics and ontologies.
A knowledge graph can be defined as a network of facts connected via explicitly defined relationships, from which new knowledge can be inferred, and a knowledge graph may have an underlying schema (a.k.a ontology) for organising the entities within the network.
There is a technology stack that underpins knowledge graphs, which unlocks countless use cases focused on tearing down data silos, richly representing data & metadata, augmenting data architecture with semantics (i.e meaning in computation form), and driving next-level AI and analytics.
Organisations across various sectors like Manufacturing, Telecommunication, IT, Mass Media, Financial Services and Pharmaceutical are applying knowledge graph technology to realise their data strategies and digital transformation. Knowledge graphs are a powerful enabler for modern data architectures integral to Industry 4.0, Digital Twins, intelligent decision support ecosystems, explainable AI, and many more.
This course is aimed at leaners, such as data-focused professionals, with an interest in the latest trends in information modelling, data architecture, knowledge representation and classification, and with no prior exposure to knowledge graph technologies. It's your guaranteed stepping stone to a solid foundation, ensured to make you become comfortable with jargon used in the field of knowledge graph, ontologies and semantics. You will also be able to articulate the importance of knowledge graphs, their underlying architecture and industry applications, as well as identify opportunities for applying 'graph thinking'.