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Teaching GuideTerm Faculty of Computer Science |
| Máster Universitario en Intelixencia Artificial |
 Subjects |
| Text Mining |
| Planning |
| Identifying Data | 2023/24 | |||||||||||||
| Subject | Text Mining | Code | 614544011 | |||||||||||
| Study programme |
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| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Official Master's Degree | 1st four-month period |
Second | Optional | 3 | ||||||||||
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| Methodologies / tests | Competencies | Ordinary class hours | Student’s personal work hours | Total hours |
| Laboratory practice | A2 A3 A4 B1 B3 B4 B6 B7 B10 C2 C3 C7 C8 | 5 | 15 | 20 |
| Supervised projects | A2 A3 A4 B1 B3 B4 B6 B7 B10 C2 C3 C7 C8 | 5 | 29 | 34 |
| Objective test | A2 A3 A4 B1 B3 B4 B6 B7 B10 C2 C3 C7 C8 | 1 | 0 | 1 |
| Guest lecture / keynote speech | A2 A3 A4 B1 B3 B4 B6 B7 B10 C2 C3 C7 C8 | 10 | 10 | 20 |
| Personalized attention | 0 | 0 | ||
| (*)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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