| Educational guide School of Engineering |
english |
| Computer Security Engineering and Artificial Intelligence (2016) |
 Subjects |
| NEURAL AND EVOLUTIONARY COMPUTATION |
| Assessment |
| IDENTIFYING DATA | 2023_24 |
| Subject | NEURAL AND EVOLUTIONARY COMPUTATION | Code | 17685106 | |||||
| Study programme |
|
Cycle | 2nd | |||||
| Descriptors | Credits | Type | Year | Period | ||||
| 4.5 | Compulsory | First | 1Q |
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| Competences | Learning outcomes | Contents |
| Planning | Methodologies | Personalized attention |
| Assessment | Sources of information | Recommendations |
| Methodologies | Competences | Description | Weight | |||||
| IT-based practicals |
|
Between four and five practical works | 90% | |||||
| Oral tests |
|
Exposition of a work | 10% | |||||
| Others |
| Other comments and second exam session | |||
|
To pass, you must submit all the activities that are proposed in class, and have a final grade above 5. An activity that does not meet the requirements of the statement, does not work correctly or is incomplete will count as a 0. The second call involves finishing and overcoming the pending parts in the first. |
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