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Teaching GuideTerm Faculty of Computer Science |
| Máster Universitario en Intelixencia Artificial |
 Subjects |
| Natural Language Understanding |
| Learning aims |
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| Identifying Data | 2022/23 | |||||||||||||
| Subject | Natural Language Understanding | Code | 614544008 | |||||||||||
| Study programme |
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| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Official Master's Degree | 1st four-month period |
First | Obligatory | 6 | ||||||||||
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| Learning outcomes | Study programme competences | ||
| To know, understand and analyze the formal representation of diverse lexical, syntactic and semantic phenomena of natural language. | AC1 |
BC1 BC3 BC4 BC6 BC10 |
CC2 CC8 |
| To know, understand and know how to use the technologies, frameworks and libraries for the construction of natural language processing systems. | AC1 AC2 |
BC3 BC4 BC6 BC7 BC10 |
CC2 CC3 CC7 |
| To design, implement and know how to use algorithms and data structures to treat and support the various phenomena characteristic of natural language. | AC1 AC2 AC3 |
BC1 BC3 BC4 BC6 BC7 BC10 |
CC2 CC3 CC7 CC8 |
| To know, understand and analyze natural language processing techniques for processing and disambiguation at the lexical, syntactic and semantic levels. | AC1 AC2 AC3 |
BC1 BC3 BC4 BC6 BC7 BC10 |
CC2 CC3 CC7 CC8 |
| To know and understand the problems posed by ambiguity and imprecision in natural language data sources and techniques to solve them. | AC1 AC2 |
BC1 BC3 BC4 BC6 BC7 BC10 |
CC2 CC3 CC7 CC8 |
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