Knowledge Graph for Beginners

This is a simple activity where you will use a visual graph to navigate through different content topics.

In this lecture, we'll go through some important ideas that are central to knowledge graphs and that we can draw out from the previous activity.

This lesson provides a concise definition for what a Knowledge Graph is.

This lesson clarifies the course structure, its intended audience and highlights all the key learning outcomes you will benefit from.

Here, you will find a decision tree diagram that will help you decide whether this course is really what you are after.

This lecture explores the idea of a network of data, which is a fundamental building block of a knowledge graph.

This lecture explores the idea of weaving data using explicitly identifiable relationships in order to bring meaning to connections.

With the interwoven 'mesh' of information, it's possible to add business rules to a knowledge graph to support knowledge discovery. This is the idea of inferable knowledge - a key strength of knowledge graph.

Knowledge graph schemas are flexible and easy to incorporate and amend. In this lecture, we introduce the concept of 'ontology', a specialist term to mean a knowledge graph schema.

This quiz will test your understanding of what a knowledge graph is.

In this activity, you will watch a short TED Talk about "A Visual History of Human Knowledge" by Manuel Lima.

This quiz will test your understanding of how knowledge has been represented and evolved over time.

This lecture explores the importance of connections and why they matter for transforming data into knowledge.

Knowledge graph owes its origin to Graph Theory. In this lecture, we briefly touch on this aspect.

Here, we will explore the different core components of the knowledge graph architecture.

In this lecture, you will be able to recognise the key differences between knowledge graph-based systems and relational database management systems.

In this lesson, we will look at the graph technology landscape. This landscape is getting busier and busier with several vendors and companies delivering various capabilities and use cases.

Agile development methodology can be applied to knowledge graph development. This lecture focuses on the Scrum methodology for developing knowledge graphs, backed by useful examples.

This is a continuation of the previous lecture looking at different approaches for when to deploy ontologies as part of the build methodology.

This quiz will test your understanding of what knowledge graph technology.

This lecture discusses the Linked Data use case.

This lecture discusses the Semantic Search use case.

This lecture discusses the Semantic Federation use case as part of the bigger theme of semantic interoperability.

This lecture discusses the Enterprise Knowledge Graph use case.

Generative AI and LLMs can hallucinate. To prevent this from happening, we can make use of knowledge graphs as part of a RAG architecture.

This lecture discusses various other use cases for knowledge graph.

This quiz will test your understanding of the applications and use cases that knowledge graphs can unlock.

This lecture touches on the place knowledge graph technology occupies in data architecture, its relevance to AI and Machine Learning, the concept of explainability, and how users are intended to consume information coming from knowledge graph through familiar views.

This is the concluding lecture for this series. Hope you've enjoyed the course!

Download course slides.

Attributions, special thanks and disclaimer.