nireEHU 
Subject
LCT at the Charles University in Prague (Czech Republic)
General details of the subject
- Mode
- Face-to-face degree course
- Language
- English
Description and contextualization of the subject
El estudiante realiza las asignaturas del 2º curso en la misma.Competencies
| Name | Weight |
|---|---|
| Conocimiento de las tecnologías del lenguaje sobre la base de los algoritmos de aprendizaje automático y aprendizaje profundo. | 100.0 % |
Study types
| Type | Face-to-face hours | Non face-to-face hours | Total hours |
|---|---|---|---|
| Lecture-based | 100 | 150 | 250 |
| Applied laboratory-based groups | 200 | 300 | 500 |
Training activities
| Name | Hours | Percentage of classroom teaching |
|---|---|---|
| Analysing and discussing papers | 125.0 | 80 % |
| Computer work practice, laboratory, site visits, field trips, external visits | 250.0 | 60 % |
| Lectures | 250.0 | 40 % |
| Seminars | 125.0 | 80 % |
Assessment systems
| Name | Minimum weighting | Maximum weighting |
|---|---|---|
| Drawing up reports and presentations | 25.0 % | 25.0 % |
| Practical tasks | 25.0 % | 25.0 % |
| Written examination | 50.0 % | 50.0 % |
Learning outcomes of the subject
* Tener conocimiento y manejo de algoritmos de aprendizaje automático* Tener criterios para diseñar experimentos para procesamiento del lenguaje
* Tener conocimiento sobre estadística inferencial con el foco en los métodos usados habitualmente en el área de la lingüística experimental
* Tener conocimientos de las técnicas principales de traducción automática en PLN, especialmente de las técnicas basadas en aprendizaje profundo.
Temary
* Foundational : Statistical methods; symbolic methods; cognition; corpus; text and speech; foundations of linguistics.* Computational Syntax and Morphology : Finite state techniques; probabilistic approaches; formal grammars; tagging, chunking; parsing.
* Computational Semantics, Pragmatics and Discourse: Syntax-semantics interface; semantic construction; dialogue; ontologies; formal semantics.
* Data Structures, Data Organization and Processing : Algebraic data-types; relational databases; semi-structured data and XML; information retrieval; digital libraries.
* Logic, Computability and Complexity: Logic and inference; automata theory; computability theory; complexity theory; discrete mathematics.
* Formal Languages and Algorithms: Formal grammars and languages hierarchy; parsing and compiler design; search techniques and constraint resolution; automated learning.
* Advanced Language Technologies: Machine translation; information and knowledge representation; information retrieval; question answering; speech recognition and generation; models of human language processing and understanding; psycholinguistics.
* Advanced Computer Science: Artificial intelligence; knowledge representation; automated reasoning; semantic web; intelligent and multi-modal interfaces; cognitive modelling; computational psychology; neural networks; machine learning.