Teaching GuideTerm Faculty of Computer Science |
Máster Universitario en Intelixencia Artificial |
Subjects |
Real Time Intelligent Systems |
Planning |
Identifying Data | 2023/24 | |||||||||||||
Subject | Real Time Intelligent Systems | Code | 614544026 | |||||||||||
Study programme |
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Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
Official Master's Degree | 2nd four-month period |
First | Optional | 3 | ||||||||||
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Methodologies / tests | Competencies / Results | Teaching hours (in-person & virtual) | Student’s personal work hours | Total hours |
Laboratory practice | A8 A9 A10 A14 A15 A16 A20 A21 A22 A23 A28 A29 A31 A30 B1 B2 B5 B6 B7 B9 B10 C2 C4 C5 C6 | 10.5 | 21 | 31.5 |
Objective test | A8 A9 A10 A14 A15 A16 A20 A21 A22 A23 A28 A29 A31 A30 B1 B2 B5 B6 B7 B9 B10 C2 C4 C5 C6 | 1.5 | 10.5 | 12 |
Guest lecture / keynote speech | A8 A9 A10 A14 A15 A16 A20 A21 A22 A23 A28 A29 A31 A30 B1 B2 B5 B6 B7 B9 B10 C2 C4 C5 C6 | 10.5 | 21 | 31.5 |
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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