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A knowledge graph is a structured representation of entities and their relationships, stored as connected nodes and edges. It helps systems reason over facts and context beyond unstructured text.
Knowledge graphs improve enterprise AI accuracy by grounding responses in curated relationships and business-specific concepts.
A pharma company links drugs, conditions, and trial outcomes in a knowledge graph to support more precise internal search.
Retrieval-Augmented Generation (RAG)
Retrieval-augmented generation is a technique that enhances a language model's responses by first retrieving relevant information from an external knowledge base, then using that information to generate a more accurate and grounded answer. It combines the strengths of search with generative AI.
Dataset
A dataset is a structured collection of data used to train, validate, or test a machine learning model. It can consist of text, images, numbers, audio, or any other type of information, typically organised into rows and columns or files and labels.
Semantic Search
Semantic search retrieves information based on meaning rather than exact keyword matches, usually by comparing embeddings in vector space.
Our programme follows a structured Level 4 curriculum with project-based learning, practical workflows, and guided implementation across business and career use cases. Funded route available for UK citizens and ILR holders.