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Teaching GuideTerm Faculty of Computer Science |
| Grao en Ciencia e Enxeñaría de Datos |
 Subjects |
| Numerical Methods for Data Science |
| Methodologies |
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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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| Methodologies | Description |
| ICT practicals | The teacher will help students deepen the concepts and numerical methods presented during the guest lectures using Python. |
| Supervised projects | Students will develop a supervised project in which they will combine the use of the different learning outcomes acquired in the subject. |
| Problem solving | Students will solve problems that help them to understand how the studied numerical methods work. |
| Objective test | There will be an exam on the dates decided by the Faculty Board. The exam will focus essentially on the solution of practical problems. |
| Collaborative learning | Students will have the opportunity to participate in a COIL project. |
| Guest lecture / keynote speech | During guest lectures, the teacher will present the different contents. She will motivate the need of the different numerical methods using real problems, and she will present the necessary concepts and different numerical methods, discussing their main features. |
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