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Teaching GuideTerm Faculty of Computer Science |
| Grao en Intelixencia Artificial |
 Subjects |
| Fundamentals of Machine Learning |
| Learning aims |
| Identifying Data | 2023/24 | |||||||||||||
| Subject | Fundamentals of Machine Learning | Code | 614G03018 | |||||||||||
| Study programme |
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| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Graduate | 2nd four-month period |
Second | Obligatory | 6 | ||||||||||
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| Learning outcomes | Study programme competences / results | ||
| Know, understand and know how to use the fundamentals of machine learning processes. | A1 A12 |
B5 B10 |
C3 |
| Know the fundamentals of regression, classification and clustering models. | A2 A12 |
B3 B7 B9 |
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| Know how to build advanced statistical models for data analysis. | A2 A12 A15 |
B7 B9 |
C3 |
| Know how to base modeling and problem solving using machine learning techniques. | A1 A2 A12 |
B5 B7 B9 |
C3 |
| Know how to build machine learning models for regression, classification and clustering. | A1 A2 A12 A15 |
B5 B7 B9 B10 |
C3 |
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