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Teaching GuideTerm Faculty of Computer Science |
| Máster Universitario en Intelixencia Artificial |
 Subjects |
| Language Modelling |
| Learning aims |
| Identifying Data | 2022/23 | |||||||||||||
| Subject | Language Modelling | Code | 614544009 | |||||||||||
| Study programme |
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| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Official Master's Degree | 2nd four-month period |
First | Optional | 3 | ||||||||||
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| Learning outcomes | Study programme competences | ||
| To know how to use the techniques and methods of natural language processing to solve real problems of analysis of texts in natural language. | AC1 AC3 |
BC1 BC3 BC4 BC7 BC10 |
CC2 CC3 CC7 |
| To know, understand and analyze deep learning techniques applied to natural language processing. | AC1 AC2 |
BC1 BC3 BC6 BC7 BC10 |
CC2 CC3 CC7 CC8 |
| To know how to use deep learning techniques and methods to solve practical problems in natural language processing. | AC1 AC2 |
BC1 BC3 BC4 BC6 BC7 BC10 |
CC2 CC3 CC7 CC8 |
| To know and understand the environmental problems posed by the computational cost of deep learning techniques when applied to text analysis | AC1 AC2 |
BC1 BC6 |
CC2 CC8 |
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