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AI4DH

Education and training

Seminars and webinars

We provide training and skill development in key areas of artificial intelligence, including deep learning, natural language processing, and explainable AI. We address the challenges and opportunities of applying AI in the digital humanities, covering topics such as data curation, dataset annotation, classification, multimedia analysis, and prompt engineering for large language models (LLMs). In addition, a dedicated course on the ethics of AI will be offered. Together, these activities address the growing need for enhanced digital skills and AI literacy among digital humanities and social sciences scholars in the era of digital transformation.

 

Are you a digital humanities and social sciences scholar and want to become proficient in using AI in your research? Here is a pathway to general AI proficiency:

First, it is essential to understand the data, as covered in the Data Management and Processing course. Next, we proceed to high-level analysis using no-code tools such as concordancers, Voyant, and Orange. After this, participants are introduced to the key concepts of machine learning, gaining at least an overview of its main techniques and approaches. Finally, they can choose to advance further by learning programming (Python, NLP) and/or exploring how to use large language models (LLMs) effectively in research contexts.

Upcoming seminars

Vibe Coding Workshop for Humanities and Social Sciences

Join us for a one-day vibe coding workshop where students and researchers in the humanities and social sciences will learn to build their own digital products and tools using the AI web app builder Lovable.

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Information retrieval from the Internet

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Previous seminars

Practical text mining in Orange

During the workshop, we will become familiar with the basic preprocessing of textual data and the transformation of documents into a vector space.

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Large Language Models for Digital Humanities: A Hands-On Introduction

This hands-on workshop introduces participants to the practical use of LLMs in research workflows. They will learn how to access and run modern LLMs locally or on GPU servers, configure them for efficient inference, and apply them to common text-based tasks. The workshop assumes basic familiarity with Python but no prior experience with machine-learning frameworks.

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Understanding large language models for digital humanities

We present the working of the transformer architecture of neural networks and focus on the decoder models, which are used in generative models, such as ChatGPT.

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Large language models for analyses in digital humanities

We explain the working of LLMs needed to understand their performance. In the context of complex phenomena analyses, we discuss the two most frequent adaptations of LLMs, fine-tuning and prompt engineering, on the example of social media analysis and folkloristics.

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