There are a number of tasks that benefit from the application of LLMs, specifically for humanists. These include:

• Searching large datasets.
• Optical Character Recognition (OCR)
• Annotation
• Part-of-speech tagging
• Topic modelling
• Translation
• Summarisation 
• Sentiment analysis
• Embeddings
• Coding, and understanding code

This page attempts to show some materials that are useful to help researchers in the humanities to address these tasks.

Training materials

• RANLP2025 conference proceedings

  • https://ranlp.org/ranlp2025/index.php/tutorials/ Includes tutorials on “Legal NLP in the LLM era” and “Building Affordable Language Models with Limited Resources”, plus a summer school on deep learning and LLMs (https://ranlp2025-summer-school.github.io/) 

• CLARIN Learning Hub https://www.clarin.eu/content/learning-hub 

  • A catalogue of 35 learning resources, example related courses are:

  • https://www.clarin.eu/content/ai-understand-and-connect-people (introductory AI concepts)

  • https://www.clarin.eu/content/processing-texts-and-corpora (Processing Texts and Corpora)

  • https://www.clarin.eu/content/natural-language-processing-methods-0 (Natural Language Processing Methods)

• Lancaster Corpus MOOC: https://www.edx.org/learn/social-sciences/lancaster-university-corpus-linguistics-and-new-technologies-data-language-society 

• Programming Historian https://programminghistorian.org/ 

  • Online tutorials in English, Spanish, French and Portuguese

  • Includes AI, machine learning tutorials in facial recognition, clustering documents, and image classification

• UCREL NLP summer schools 2024 GitHub repositories: https://github.com/UCREL/USS2024 

  • These are summer schools which ran in 2024 aimed at computer scientists and early career NLP researchers, and includes several practical sessions which are LLM related

• ARISA AI Skills Academy https://academy.aiskills.eu/courses (recommended by CLARIN training hub)

  • Aimed at a wide variety of learners with courses providing an introduction to AI, machine learning, classification, deep learning, and explainability

• AI & Machine Learning in Libraries: a LIBER Digital Scholarship & Data Science Topic Guide for Library Professionals https://libereurope.github.io/ds-topic-guides/ai-ml.html 

• #dariahTeach was initially funded by an ERASMUS+ Strategic Partnership (2015-2017) 

  • Text Analysis is a four unit course on text analysis and corpus linguistics https://teach.dariah.eu/course/view.php?id=78 

• TRAM511 Introduction to Artificial Intelligence for Translators and Interpreters https://www.surrey.ac.uk/cpd-and-short-courses/tram511-introduction-artificial-intelligence-translators-and-interpreters 

• University internal training programmes 

• Library Carpentry courses (e.g. Text and Data Mining: https://librarycarpentry.github.io/lc-tdm/)

• Course: AI for Social Sciences and Humanities | OpenCourses-UoC

  • Introductory online course assuming no prior technical knowledge

• MOOC: AI in Society | Una Europa