Course Overview

Academic year: *

Course title: Análisis, gestión y proyectos en Patrimonio Industrial

Dates: 19 January to 16 November (according to modules)

Enrollment period: 7 September to 15 January (registration not open)

Eligibility Requirements

Admission is limited to programs offering Master's degree or equivalent titles.

Applicants must possess a university degree such as licence, graduate, diploma, technical engineer, or architectural technical degree, or an equivalent foreign qualification.

The equivalence of foreign degrees is evaluated by the Vice-rectorate, based on the course director's report.

Exceptional cases may waive the degree requirement if the candidate presents a professional curriculum demonstrating the necessary skills.

This is subject to the Vice-rectorate's approval and the course director's recommendation.

Target Audience

The program is open to professionals and scholars interested in industrial heritage, its management, conservation, and administration, from private and public sectors, and from any professional background (humanities,



socio-economic, legal, scientific, or technical).

Graduated university students, engineers, architects, and specialists are highly recommended.

Course Objectives

Provide a systematic and up-to-date overview of industrial heritage knowledge.

Cover models of heritage management and direction within the industrial context.

Train participants in the techniques for studying, presenting, reconstructing, assessing, and acting on all categories of industrial heritage assets.

Sequence the content logically across the three academic formats (Open Teaching, University Expert, Master's).

Modules and Credits

Module 01 - Bases industriales del Patrimonio Cultural (10 ECTS), 19 January to 7 June , €

Module 02 - Análisis del Patrimonio Industrial (10 ECTS), 19 January to 7 June , €

Module 03 - Normativas, programas e iniciativas en Patrimonio Industrial (10 ECTS), 19 January to 7 June , €

Module 04

📌 Industrial Heritage: Analysis (Tapachula de Córdova y Ordoñez)
🏢 Máster en Estadística Aplicada con R y Python (UNED)
📍 Tapachula de Córdova y Ordoñez