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Teaching GuideTerm Faculty of Computer Science |
| Máster Universitario en Intelixencia Artificial |
 Subjects |
| Explainable and Trustworthy AI |
| Learning aims |
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| Identifying Data | 2022/23 | |||||||||||||
| Subject | Explainable and Trustworthy AI | Code | 614544004 | |||||||||||
| Study programme |
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| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Official Master's Degree | 2nd four-month period |
First | Obligatory | 3 | ||||||||||
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| Learning outcomes | Study programme competences | ||
| Develop capacities for an adequate treatment of privacy, reliability, transparency and interpretability of models and results | AC5 AC6 AC7 AC8 |
BC1 BC2 BC3 BC6 BC7 BC8 BC9 |
CC2 CC3 CC4 CC5 CC6 CC7 CC8 |
| Identify and analyze biases and their impact on the design of Artificial Intelligence algorithms | AC5 AC6 AC7 AC8 |
BC1 BC2 BC3 BC6 BC7 BC8 BC9 |
CC2 CC3 CC4 CC5 CC6 CC7 CC8 |
| Know and understand the social and ethical implications of technology in general and Artificial Intelligence in particular | AC5 AC6 AC7 AC8 |
BC1 BC2 BC3 BC6 BC7 BC8 BC9 |
CC2 CC3 CC4 CC5 CC6 CC7 CC8 |
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