|
Teaching GuideTerm Faculty of Computer Science |
| Máster Universitario en Intelixencia Artificial |
 Subjects |
| Real Time Intelligent Systems |
| Planning |
| Identifying Data | 2022/23 | |||||||||||||
| Subject | Real Time Intelligent Systems | Code | 614544026 | |||||||||||
| Study programme |
|
|||||||||||||
| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Official Master's Degree | 2nd four-month period |
First | Optional | 3 | ||||||||||
|
||||||||||||||
| Methodologies / tests | Competencies | Ordinary class hours | 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. | ||||
|
