University of Turin

What you'll study

This programme blends theoretical and practical training in computational linguistics, natural language processing (NLP) and digital humanities methods. Core themes include corpus linguistics, text mining, machine learning for language, speech and multimodal data processing, and digital scholarly editing.

• Foundations of Language Technologies: formal and computational approaches to morphology, syntax and semantics; introduction to NLP toolkits and pipelines.
• Machine Learning for Language: supervised and unsupervised methods, neural networks and representation learning applied to text and speech.
• Corpus Methods and Annotation: corpus design, linguistic annotation, metadata standards, inter-annotator agreement and searching large textual datasets.
• Digital Scholarly Editing and TEI: principles of digital editions, text encoding (TEI), editorial workflows and versioning for historical sources.
• Text Mining and Information Extraction: named entity recognition, relation extraction, topic modelling and sentiment analysis.
• Multimodal and Speech Technologies: basics of speech processing, alignment of audio and text, and multimodal corpora.
• Programming and Tools: practical courses in Python/R, use of NLP libraries, database handling, web scraping and visualization for humanities data.
• Project Work and Dissertation: supervised applied projects with options for internships in cultural institutions, libraries or industry, culminating in a research dissertation or applied prototype.

Teaching methods typically combine lectures, hands-on laboratories, seminars and project supervision. Students learn to work with real-world datasets, create reproducible workflows, and deploy pipelines for analysis and digital publication.

Entry requirements

Applicants are normally expected to hold a first-cycle degree (Bachelor's) or equivalent in a relevant subject such as linguistics, computer science, information science, digital humanities, philology, modern languages, or a closely related field. Candidates with degrees in other disciplines but with demonstrable quantitative and programming skills may also be considered.

• A solid grounding in at least one programming language (commonly Python) and basic statistics or machine learning concepts is required.
• Prior coursework or experience in linguistics, corpus work, or text analysis is highly desirable.
• Proficiency in English is required for instruction and assessment; evidence may be requested from applicants whose first language is not English. Knowledge of Italian is beneficial for local internships and archival work but is not always mandatory.
• Applications usually require academic transcripts, a CV, a statement of purpose outlining relevant experience and interests, and references. Some applicants may be invited for an interview or to submit a short technical task.

Career prospects

Graduates combine humanities expertise with computational skills and are prepared for roles across academia, cultural heritage and industry. Typical career paths include:

• Computational linguist or NLP engineer in technology companies and start-ups.
• Digital humanist, digital curator or project manager in museums, archives and libraries, working on digitisation, annotation and online presentation of cultural assets.
• Data analyst or text mining specialist in publishing, media, social research and public institutions.
• Localization and language technology roles in translation and localisation firms.
• Research positions or doctoral study in computational linguistics, digital humanities or related interdisciplinary fields.

Why study at University of Turin

The University of Turin offers a strong interdisciplinary environment where departments of linguistics, computer science and humanities collaborate on language and cultural heritage projects. Students benefit from hands-on laboratory courses, access to digitised collections and computational facilities, and opportunities to work with local archives, libraries and research groups.

The programme emphasises applied skills and reproducible research practices, preparing students to operate at the intersection of technology and the humanities. Its location in a city with rich cultural institutions also supports practical internships and partnerships that help bridge academic training and professional experience.