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Teaching GuideTerm Faculty of Computer Science |
| Máster Universitario en Intelixencia Artificial |
 Subjects |
| Language Modelling |
| Methodologies |
| Identifying Data | 2022/23 | |||||||||||||
| Subject | Language Modelling | Code | 614544009 | |||||||||||
| Study programme |
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| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Official Master's Degree | 2nd four-month period |
First | Optional | 3 | ||||||||||
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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 in advance and the teacher will promote an active attitude, asking questions that allow clarifying specific aspects and leaving questions open for the student's reflection. |
| Laboratory practice | Practical classes with the use of a computer, which allow the student to familiarize himself/herself from a practical point of view with the issues exposed in the theoretical classes. |
| Problem solving | Problem-based learning, seminars, case studies and projects. |
| Multiple-choice questions | Brief questionnaires to be filled after some theoretical sessions to help assimilate the content of the lecture. |
| Objective test | The mastery of the theoretical and operating knowledge of the subject will be evaluated. |
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