Certified Professional in Digital Humanities Text Encoding
-- viendo ahoraCertified Professional in Digital Humanities Text Encoding (CP-DHTe) certification validates expertise in encoding texts for digital humanities research. It's for scholars, librarians, and archivists.
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Detalles del Curso
- TEI XML Fundamentals: Introduction to Text Encoding Initiative (TEI) Guidelines and XML for digital humanities projects.
- Schema Design and Implementation: Creating and using TEI schemas for structured text encoding.
- Metadata and Encoding Best Practices: Implementing Dublin Core and other metadata schemas, along with best practices for text encoding.
- XSLT Transformations and Data Visualization: Using XSLT to transform TEI XML data and create visualizations.
- Digital Text Encoding Projects: Case Studies and Examples: Examining real-world TEI projects and best practices.
- Advanced TEI Elements: Deep dive into complex TEI elements for representing nuanced textual features.
- Working with Digital Libraries and Repositories: Understanding the workflow for importing and exporting TEI XML data from digital libraries.
- Text Analysis Techniques for Encoded Texts: Using TEI-encoded data for computational text analysis.
Trayectoria Profesional
Career Role Description Digital Humanities Text Encoding Specialist Develops and implements text encoding strategies for digital humanities projects, focusing on XML and TEI .
High demand for expertise in metadata creation and schema design.
Digital Humanities Project Manager (Text Encoding Focus) Manages teams working on large-scale text encoding initiatives, ensuring adherence to best practices in text analysis and data curation .
Strong project management and leadership skills are essential.
Research Associate (Digital Text Encoding) Conducts research using digitally encoded texts, employing computational methods for analysis.
Requires strong analytical and programming skills (e.g., Python).
Data Scientist (Digital Humanities) Applies data science techniques to large text corpora, extracting insights and creating visualizations.
Requires advanced skills in statistical modeling and machine learning .
Requisitos de Entrada
- Comprensión básica de la materia
- Competencia en idioma inglés
- Acceso a computadora e internet
- Habilidades básicas de computadora
- Dedicación para completar el curso
No se requieren calificaciones formales previas. El curso está diseñado para la accesibilidad.
Estado del Curso
Este curso proporciona conocimientos y habilidades prácticas para el desarrollo profesional. Es:
- No acreditado por un organismo reconocido
- No regulado por una institución autorizada
- Complementario a las calificaciones formales
Recibirás un certificado de finalización al completar exitosamente el curso.
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Tarifa del curso
- 3-4 horas por semana
- Entrega temprana del certificado
- Inscripción abierta - comienza cuando quieras
- 2-3 horas por semana
- Entrega regular del certificado
- Inscripción abierta - comienza cuando quieras
- Acceso completo al curso
- Certificado digital
- Materiales del curso
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