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Teaching GuideTerm Faculty of Computer Science |
| Grao en Ciencia e Enxeñaría de Datos |
 Subjects |
| Natural Language Processing and Text Mining |
| Planning |
| Identifying Data | 2022/23 | |||||||||||||
| Subject | Natural Language Processing and Text Mining | Code | 614G02043 | |||||||||||
| Study programme |
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| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Graduate | 2nd four-month period |
Fourth | Optional | 6 | ||||||||||
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| Methodologies / tests | Competencies | Ordinary class hours | Student’s personal work hours | Total hours |
| Guest lecture / keynote speech | A28 B3 B8 B9 | 21 | 21 | 42 |
| Laboratory practice | A28 B2 B4 B7 B9 B10 | 10 | 30 | 40 |
| Problem solving | A28 B2 B3 B8 | 8 | 30 | 38 |
| Objective test | A28 B2 B3 B8 | 2 | 10 | 12 |
| Supervised projects | A28 B3 B4 B7 B10 | 1 | 16 | 17 |
| Personalized attention | 1 | 0 | 1 | |
| (*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students. | ||||
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