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Teaching GuideTerm Faculty of Computer Science |
| Máster Universitario en Intelixencia Artificial |
 Subjects |
| Deep Learning |
| Planning |
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| Identifying Data | 2022/23 | |||||||||||||
| Subject | Deep Learning | Code | 614544013 | |||||||||||
| Study programme |
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| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Official Master's Degree | 2nd four-month period |
First | Optional | 6 | ||||||||||
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| Methodologies / tests | Competencies | Ordinary class hours | Student’s personal work hours | Total hours |
| Guest lecture / keynote speech | A11 A12 A13 B2 B3 B6 B8 B9 C4 C8 | 21 | 21 | 42 |
| Laboratory practice | A11 A12 A13 A16 B2 B3 B4 B5 B6 B7 B8 B9 C3 C7 C9 | 21 | 84 | 105 |
| Objective test | A11 A12 B7 B9 | 3 | 0 | 3 |
| 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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