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Teaching GuideTerm Faculty of Computer Science |
| Máster Universitario en Intelixencia Artificial |
 Subjects |
| Natural Language Understanding |
| Methodologies |
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| Identifying Data | 2022/23 | |||||||||||||
| Subject | Natural Language Understanding | Code | 614544008 | |||||||||||
| Study programme |
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| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Official Master's Degree | 1st four-month period |
First | Obligatory | 6 | ||||||||||
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| Methodologies | Description |
| Guest lecture / keynote speech | Theoretical classes, in which the content of each topic is exposed. The student will have copies of the slides beforehand and the professor will promote an active attitude, asking questions to clarify specific aspects and leaving open questions for the student's reflection. |
| Laboratory practice | Practical classes with the use of computers, which allow the student to familiarize himself/herself from a practical point of view with the issues presented in the theoretical classes. |
| Problem solving | Problem-based learning, seminars, case studies and projects. |
| Objective test | The mastery of the theoretical and operating knowledge of the subject will be evaluated. |
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