Teaching GuideTerm Faculty of Computer Science |
Máster Universitario en Intelixencia Artificial |
Subjects |
Explainable and Trustworthy AI |
Learning aims |
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Identifying Data | 2023/24 | |||||||||||||
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 / results | ||
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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