I UNIVERSITY EXTENSION DIPLOMA IN

DIGITAL METHODOLOGIES AND COMPUTATIONAL APPROACHES TO RESEARCH IN THE HUMANITIES

This University Extension Diploma introduces students and professionals in the humanities and related disciplines to the main digital methods and computational approaches currently being used in humanities and cultural research, combining theoretical foundations, training in the use of tools, and practical exercises applied to cultural data and issues.

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Aimed particularly at students and graduates in the Humanities, Fine Arts and Social Sciences, as well as professionals in the cultural sector who are interested in integrating digital approaches and AI into their research or professional practice.

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An introductory yet thorough approach

No previous programming experience is required; the course starts from scratch in terms of computing, with ongoing support and exercises tailored to students with a background in the humanities.

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Format and duration

A 30 ECTS University Extension Diploma, delivered online, with synchronous sessions in the afternoons, making it easier to combine with other studies or work commitments.

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Duration and price

The course will run from 10 October 2026 to 10 June 2027. The total course fee is 550 euros and can be paid in two instalments.

Limited places available

Between 32 and 40 places, allowing for close monitoring of students’ progress and their projects. Don’t wait any longer – book your place!

RELEVANT INFORMATION

Academic and Administrative Information
Number of places 40
Price 550,00 €
Pre-registration deadline From 1 June 2026 to 25 September 2026
Pre-enrolment payment date Until 28 September 2026 (Amount: €275.00)
Enrolment deadline From 1 September 2026 to 28 September 2026
Payments and deadlines 1st instalment: €275.00 (Deadline: by 15 December 2026)
Course dates From 10 October 2026 to 10 June 2027
Venue and Format ONLINE
Timetable Afternoon slots for synchronous sessions. These sessions can also be attended on a delayed basis
Entry requirements There are no specific requirements
Online Teaching 30.00 ECTS
Total European credits 3.00 ECTS

What you’ll learn on this course

Upon completing this course, you will be able to understand the fundamentals of digital methodologies applied to research in the humanities and to contextualise them within the current transformation of the cultural field. You will develop practical skills using tools and languages such as Python, geographic information systems, network analysis techniques, photogrammetry, immersive narratives and natural language processing methods, always drawing on real-world examples and case studies.

You will learn to work with different types of cultural data (text, images, metadata, spatial data), to structure and analyse them critically, and to assess the possibilities and limitations of computational methodologies in relation to research questions in the humanities. Furthermore, you will develop an interdisciplinary perspective that links the humanities with computer science, mathematics, statistics and information science, and you will be equipped with guidelines for conceptualising and designing your own research project based on digital approaches.

Why is it important to undertake this training?

In recent years, the field of the humanities has undergone a profound transformation with the integration of digital and computational technologies into research, teaching and cultural management. However, most humanities degree programmes do not systematically include training in these methodologies, creating a gap between traditional practices and the new possibilities for analysis and knowledge creation.

This course addresses this need by offering a structured introduction to the most widely used digital methods in the Humanities today, designed specifically for those with no prior technical training. It provides skills that are valuable both in the academic sphere (research projects, undergraduate dissertations, postgraduate dissertations, theses) and in the professional sphere, particularly in cultural institutions, archives, libraries, museums, publishing houses and digital heritage projects, where the ability to manage, analyse and interpret large volumes of cultural data, as well as the innovative and creative use of artificial intelligence, is increasingly valued.

How is this university extension diploma structured?

The programme has not been designed as a mere series of courses on tools, but rather as a pathway aimed at understanding how to develop a humanistic or cultural project based on computational and digital methods. Its main distinguishing feature is the integration of technical decisions into the entire intellectual and methodological process: from the formulation of new research questions to the identification and structuring of data, the reasoned selection of methods, the design of analytical strategies and the critical interpretation of results. The course culminates in a module dedicated to designing a student’s own digital project, from defining the problem to articulating its objectives, sources, data, methods and analysis strategies.

This guidance may be particularly useful for students who are starting to consider their Final-year undergraduate projects, final-year master’s projects or doctoral theses, as well as for researchers and professionals who wish to develop competitive projects, teaching innovation initiatives or proposals relating to cultural management, mediation and dissemination.

Objectives

  • To understand the fundamentals and development of the digital methodologies applied to research in the humanities and the cultural sphere.
  • Develop practical skills in digital and computer-based tools specific skills (e.g. Python, GIS, network analysis, photogrammetry, applied AI), geared towards humanities and cultural projects.
  • To encourage critical analysis cultural data and the results derived from digital methods, identifying their opportunities and limitations for the humanities and the cultural sector.
  • Promoting interdisciplinarity, linking the humanities with computer science, mathematics, statistics and information science.
  • To introduce students to the project conceptualisation and design research projects based on digital and computational methodologies.

Credit recognition

Credits successfully completed on this institution-specific qualification may be recognised for academic credit towards official university qualifications, in accordance with Article 10 of Royal Decree 822/2021 of 28 September. Recognition must be applied for at the host university, which will decide in accordance with its own regulations on the recognition and transfer of credits, and requires a close correspondence between the competences accredited in the institution’s own degree and those of the corresponding official degree. Generally speaking, the number of credits that can be recognised may not exceed 15 % of the total credits in the curriculum.

Programme

  1. Introduction and general concepts regarding digital methodologies in the Humanities
    It presents the context, history and main approaches of digital methodologies in the humanities, as well as examples of projects and critical debates on their implications and challenges.

  2. An Introduction to the Python Programming Language for Humanities Scholars and Strategies for vibe coding*
    It provides basic computer literacy using Python, familiarisation with environments such as Google Colab, and experience of working with different types of cultural data, including the critical use of AI systems to generate and adapt code.

  3. Research using cultural data: collection, structuring and analysis
    It covers how to identify, collect, clean and organise data from archives, libraries, museums, digital collections and online platforms, as well as initial analysis techniques geared towards humanities research questions.

  4. Cultural analytics based on network and systems analysis
    It introduces network analysis as applied to cultural contexts (networks of actors, works, institutions and the circulation of content), and demonstrates how these techniques enable the exploration of complex patterns and relationships in the humanities

  5. Geospatial data: Geographic Information Systems (GIS) in the Humanities
    It explains the use of GIS to map cultural, historical and heritage phenomena, integrating spatial data with other sources to generate meaningful visualisations and geographical analyses.

  6. Photogrammetry and its applications in the cultural sector
    It introduces the principles of photogrammetry and its application to the documentation, preservation and study of cultural and heritage assets using three-dimensional models.

  7. Virtualisation and immersive narratives in the cultural sphere
    Explore how virtualisation technologies and immersive environments enable the creation of new ways of narrating, experiencing and communicating heritage and cultural content.

  8. Computational methods for language processing
    It introduces basic natural language processing techniques applied to humanities text corpora, with examples of semantic, stylistic and thematic analysis supported by computational tools.

  9. Applied artificial intelligence: computer vision, multimodal models and generative AI
    It explores applications of AI in the analysis of images, texts and multimodal cultural data, as well as the possibilities and risks of generative AI in the humanities.

  10. How to conceptualise and design a digital research project
    Guides students through the design of a research project based on digital and computational methodologies, from the formulation of research questions to the selection of data, methods and analysis strategies.

Faculty

Nuria Rodríguez Ortega

Nuria Rodríguez Ortega

PhD in Art History. University of Málaga

María Marcos Cobaleda

María Marcos Cobaleda

PhD in Art History. University of Málaga

Antonio Moreno Ortiz

Antonio Moreno Ortiz

PhD in English Language and Literature. University of Málaga

Pedro Luego Gutiérrez

Pedro Luego Gutiérrez

PhD in Art History. University of Seville

María Ortiz Tello

Maria Ortiz Tello

PhD in Art History. UNIR

Bárbara Romero Ferrón

Bárbara Romero Ferrón

PhD in Art History. University of Utrecht

Alejandro Mozo Quesada

Alejandro Mozo Quesada

Bachelor’s degree in Computer Engineering. University of Málaga

Ángel Lumbreras Fernández

Ángel Lumbreras Fernández

FPU pre-doctoral research fellow. University of Málaga

David  Ruiz Torres

David Ruiz Torres

PhD in Art History. University of Málaga

Gizéh Rangel de Lázaro

Gizéh Rangel de Lázaro

Ramón y Cajal Fellow. University of Málaga.

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