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Teaching GuideTerm Faculty of Computer Science |
| Grao en Ciencia e Enxeñaría de Datos |
 Subjects |
| Numerical Methods for Data Science |
| Learning aims |
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| Identifying Data | 2023/24 | |||||||||||||
| Subject | Numerical Methods for Data Science | Code | 614G02033 | |||||||||||
| Study programme |
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| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Graduate | 1st four-month period |
Fourth | Optional | 6 | ||||||||||
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| Learning outcomes | Study programme competences | ||
| Identify the potential of numerical methods in the solution of problems from data science. | A2 |
B2 B3 B4 B8 B9 |
C1 C4 |
| Understand the basis of numerical methods to be able to apply them with criteria, not being a mere user of the options of a software package as a black box. | A2 |
B2 B3 B4 B7 B8 B9 |
C1 C4 |
| Be able to decide which numerical methods can be applied to solve each problem and which ones are the most efficient. Have the basis to learn more advanced methods. | A2 |
B2 B3 B4 B7 B8 B9 |
C1 C4 |
| Manage software tools that implement the numerical methods studied and acquire the ability to implement them and make extensions. | A2 |
B2 B4 B9 B10 |
C1 C4 |
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