Teaching GuideTerm Faculty of Computer Science |
Grao en Ciencia e Enxeñaría de Datos |
Subjects |
Regression Models |
Planning |
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Identifying Data | 2020/21 | |||||||||||||
Subject | Regression Models | Code | 614G02012 | |||||||||||
Study programme |
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Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
Graduate | 1st four-month period |
Second | Obligatory | 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 | A17 A18 B3 B8 B9 B10 | 30 | 30 | 60 |
ICT practicals | A17 A18 A20 B2 B3 B8 B9 C1 | 20 | 20 | 40 |
Seminar | A18 A20 B2 B3 B8 C1 | 10 | 10 | 20 |
Problem solving | A17 A18 A20 B2 B7 B9 C1 | 0 | 20 | 20 |
Objective test | A17 A18 A20 B2 B9 C1 | 6 | 0 | 6 |
Personalized attention | 4 | 0 | 4 | |
(*)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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