Linguistic computing

The Faculty of Linguistic Sciences and Foreign Literatures offers the possibility of accessing the LM-39 graduate programme class in Linguistics, with a specific graduate programme in Linguistic Computing. This graduate programme represents the continuation and crowning, at a higher degree of critical consciousness and operational capacity, of the undergraduate degree and the respective curricula.
In light of the identity of our University, the Faculty's teaching and cultural and scientific training are oriented towards the preparation of professionals capable of intervening effectively in work contexts where high-level competence in the (automatic) analysis of linguistic data is required. A mature interdisciplinary linguistic-computational competence is, in fact, increasingly required in professional contexts that make use of linguistically mediated information recorded on digital support.
The constant evolution of the world of work, with the development of new sectors and new professional profiles, is in fact closely followed by the Faculty, which is always ready to adapt its educational offer (both in terms of the content of the courses and the general organization of the degree programmes) to the needs of companies, organisations and institutions in which future graduates will be called upon to work.

The English Graduate Programme in Linguistic Computing provides an advanced knowledge of the problems, methods, techniques and tools related to the automatic processing of linguistic data. This knowledge is combined with the acquisition of skills in linguistic theory and methodology, as well as in the new languages of communication and information. Similarly to other programmes in Speech & Language Processing, Computational Linguistics, Digital Humanities, or Computer Science Humanities, active at national and international level, the degree programme in Linguistic Computing prepares professionals such as experts in automatic processing of linguistic data, planning, production and analysis of content for the Web, Digital Transformation and Customer Interaction.
The normal duration of the graduate degree programme is an additional two years after graduation.
In addition to deepening the knowledge of two foreign languages, the structure of the degree programme includes a study plan that, in the first year, provides students with the theoretical, methodological and instrumental foundations of automatic linguistic analysis. In the second year, the acquired skills are put into practice in terms of the development and application of automatic language processing tools in specific sectors.
Laboratories, practical activities and the possibility of conducting internships with a wide range of social partners, at national and international level, are an integral part of this application phase, by virtue of the expendability of the skills acquired in terms independent of the language subject to automatic analysis.

The educational objective of the Graduate Degree Programme in Linguistic Computing is to provide students with the mastery of the following skills, knowledge and abilities:

•  in-depth knowledge of the theoretical, methodological and applicative aspects related to automatic language processing;
• ability to manage, structure and distribute large sets of linguistic data and metadata to support the automatic analysis of their semantic content;
• ability to acquire the methodologies and skills necessary to hold positions of responsibility in the areas dedicated to marketing, communication and operational innovation in companies and institutions characterized by new digital business models;
• proficiency in at least two of the major European or non-European languages.

The graduate degree programme in Linguistic Computing is taught in blended mode, with a ratio of face-to-face to online classes of 60:40. Online classes can take place either synchronously, that is, with the active participation of students in real time, or asynchronously, allowing students to access materials and recordings as needed.

The semester is structured with weeks 1 and 2 entirely devoted to in-person lectures. Week 3,4, and 5 alternate in-person and online lectures. Week 6 is reserved for midterm tests, which are scheduled for some teachings.