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Teaching GuideTerm Faculty of Computer Science |
| Máster Universitario en Intelixencia Artificial |
 Subjects |
| AI in Big Data Environments |
| Methodologies |
| Identifying Data | 2023/24 | |||||||||||||
| Subject | AI in Big Data Environments | Code | 614544016 | |||||||||||
| Study programme |
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| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Official Master's Degree | 1st four-month period |
Second | Optional | 6 | ||||||||||
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| Methodologies | Description |
| ICT practicals | Practical classes in the computer classroom, which allow the student to familiarize himself/herself from a practical point of view with the issues exposed in the theoretical classes. |
| Supervised projects | Learning based on problems, seminars, case studies or projects, which allow students to acquire certain competences based on the resolution of exercises competencies based on the resolution of exercises, case studies and projects. |
| Objective test | Test in which the student must demonstrate the acquired knowledge from the course |
| Guest lecture / keynote speech | Theory classes, in which the content of each topic is exposed. The student will have copies of the transparencies beforehand and the professor will promote an active attitude, asking questions to clarify specific aspects and leaving open questions for the student's reflection |
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