Teaching GuideTerm Faculty of Computer Science |
Máster Universitario en Intelixencia Artificial |
Subjects |
AI Fundamentals |
Planning |
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Identifying Data | 2022/23 | |||||||||||||
Subject | AI Fundamentals | Code | 614544001 | |||||||||||
Study programme |
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Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
Official Master's Degree | 1st four-month period |
First | Obligatory | 3 | ||||||||||
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Methodologies / tests | Competencies / Results | Teaching hours (in-person & virtual) | Student’s personal work hours | Total hours |
Laboratory practice | A5 A17 B1 B2 B3 B4 B5 B6 B7 B8 C2 C3 C4 C6 C7 C8 C9 | 7 | 21 | 28 |
Problem solving | A5 A17 B1 B2 B3 B4 B5 B6 B7 B8 C2 C3 C4 C6 C7 C8 C9 | 4 | 23 | 27 |
Guest lecture / keynote speech | A5 A17 B1 B2 B3 B4 B5 B6 B7 B8 C2 C3 C4 C6 C7 C8 C9 | 10 | 9 | 19 |
Personalized attention | 1 | 0 | 1 | |
(*)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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