What is the Autumn School about?

The Autumn School introduces participants to the latest developments in Knowledge Graphs, Semantic Technologies, and Artificial Intelligence. Combining theory with hands-on sessions, the programme explores how semantic technologies and Large Language Models (LLMs) can be used to integrate data, extract knowledge from unstructured information, and build intelligent, trustworthy AI systems.

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Content and Objective

The programme provides a balanced mix of theoretical foundations and practical applications. Participants will learn the basics of Knowledge Graphs and Virtual Knowledge Graphs, explore semantic data integration, discover AI techniques such as embeddings and LLMs, and gain hands-on experience with tools for knowledge extraction and trustworthy AI.

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The four macro-areas

• Knowledge Graph Foundations – Introduction to Knowledge Graphs, ontologies, and semantic technologies.

• Semantic Data Integration – Virtual Knowledge Graphs, data mappings, SPARQL, and practical tools.

• AI for Knowledge Engineering – Embeddings, Transformers, LoRA, and Large Language Models.

• Trustworthy AI – Information extraction pipelines and the development of reliable AI systems.

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Audience and language

The Autumn School is intended for Master’s students, PhD candidates, researchers, and professionals interested in Knowledge Graphs, Semantic Technologies, and Artificial Intelligence.

The official language of the Autumn School is English.