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Teaching GuideTerm Faculty of Computer Science |
| Grao en Enxeñaría Informática |
 Subjects |
| Machine Learning |
| Planning |
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| Identifying Data | 2019/20 | |||||||||||||
| Subject | Machine Learning | Code | 614G01038 | |||||||||||
| Study programme |
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| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Graduate | 2nd four-month period |
Third | Optional | 6 | ||||||||||
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| Methodologies / tests | Competencies | Ordinary class hours | Student’s personal work hours | Total hours |
| Guest lecture / keynote speech | A45 C7 C8 | 21 | 42 | 63 |
| Laboratory practice | A45 B1 B9 | 12 | 24 | 36 |
| Supervised projects | A45 C2 C6 | 7 | 19 | 26 |
| Objective test | A45 C8 C7 | 2 | 20 | 22 |
| Personalized attention | 3 | 0 | 3 | |
| (*)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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