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Teaching GuideTerm Faculty of Computer Science |
| Grao en Intelixencia Artificial |
 Subjects |
| Fundamentals of Machine Learning |
| Planning |
| Identifying Data | 2023/24 | |||||||||||||
| Subject | Fundamentals of Machine Learning | Code | 614G03018 | |||||||||||
| Study programme |
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| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Graduate | 2nd four-month period |
Second | Obligatory | 6 | ||||||||||
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| Methodologies / tests | Competencies | Ordinary class hours | Student’s personal work hours | Total hours |
| Guest lecture / keynote speech | A12 A15 B5 B9 B10 C3 | 30 | 38 | 68 |
| Laboratory practice | A1 A2 B3 B7 C3 | 15 | 24 | 39 |
| Supervised projects | A1 A2 A15 B3 B7 B10 | 15 | 24 | 39 |
| Objective test | A1 A12 B5 B7 B10 | 2 | 0 | 2 |
| Personalized attention | 2 | 0 | 2 | |
| (*)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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