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 / Results | Teaching hours (in-person & virtual) | 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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