Teaching GuideTerm Faculty of Computer Science |
Máster Universitario en Intelixencia Artificial |
Subjects |
Deep Learning |
Learning aims |
|
|
|
Identifying Data | 2022/23 | |||||||||||||
Subject | Deep Learning | Code | 614544013 | |||||||||||
Study programme |
|
|||||||||||||
Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
Official Master's Degree | 2nd four-month period |
First | Optional | 6 | ||||||||||
|
Learning outcomes | Study programme competences / results | ||
To understand the functioning of Artificial Neuron Networks. | AC10 AC11 |
CC8 CC9 |
|
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 |
|