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Teaching GuideTerm Faculty of Computer Science |
| Máster Universitario en Intelixencia Artificial |
 Subjects |
| Deep Learning |
| Learning aims |
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| Identifying Data | 2022/23 | |||||||||||||
| Subject | Deep Learning | Code | 614544013 | |||||||||||
| Study programme |
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| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Official Master's Degree | 2nd four-month period |
First | Optional | 6 | ||||||||||
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| Learning outcomes | Study programme competences | ||
| To understand the functioning of Artificial Neuron Networks. | AC10 AC11 |
CC8 CC9 |
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| Be able to design Deep Learning architectures | AC10 AC11 AC12 AC15 |
BC2 BC3 BC4 BC5 BC6 BC7 BC8 BC9 |
CC4 CC7 CC8 CC9 |
| Be able to obtain models capable of pattern classification and image recognition. | AC10 AC11 AC15 |
BC2 BC3 BC4 BC6 BC7 BC8 BC9 |
CC3 CC4 CC8 CC9 |
| Be able to visualize and analyze the learning information of a Deep Learning architecture. | AC10 AC11 |
BC4 BC9 |
CC8 CC9 |
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