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Teaching GuideTerm Faculty of Computer Science |
Guía Provisional
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| Grao en Ciencia e Enxeñaría de Datos |
 Subjects |
| Machine Learning II |
| Planning |
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| Identifying Data | 2024/25 | |||||||||||||
| Subject | Machine Learning II | Code | 614G02021 | |||||||||||
| Study programme |
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| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Graduate | 1st four-month period |
Third | Obligatory | 6 | ||||||||||
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| Methodologies / tests | Competencies / Results | Teaching hours (in-person & virtual) | Student’s personal work hours | Total hours |
| Supervised projects | A24 A25 A26 A28 A1 A3 B2 B3 B7 B9 B10 C1 | 5 | 25 | 30 |
| Objective test | A24 A25 A1 A3 B7 | 3 | 21 | 24 |
| ICT practicals | A24 A25 A26 A28 B3 B10 C1 | 16 | 16 | 32 |
| Guest lecture / keynote speech | A24 A25 A26 A1 A3 B2 B3 B8 C4 | 21 | 42 | 63 |
| 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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