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Teaching GuideTerm Faculty of Computer Science |
| Máster Universitario en Intelixencia Artificial |
 Subjects |
| Intelligent Robotics I |
| Methodologies |
| Identifying Data | 2023/24 | |||||||||||||
| Subject | Intelligent Robotics I | Code | 614544019 | |||||||||||
| Study programme |
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| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Official Master's Degree | 1st four-month period |
First | Obligatory | 3 | ||||||||||
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| Methodologies | Description |
| Supervised projects | Practices in which some of the techniques seen in the theoretical classes on robot simulation environments and the robotic platforms selected by the teachers of the assignment will be implemented. These works will be carried out by the students autonomously and their progress will be tutored by the teachers. |
| Guest lecture / keynote speech | Oral presentation by the teachers of the theoretical subject. This methodology can be hybridized with a collaborative learning methodology. |
| Seminar | Practical programming classes in which the basic tools used in the tutored work will be explained: simulator and programming libraries. |
| Document analysis | Methodological technique that involves the use of audiovisual and/or bibliographic documents relevant to the subject matter with activities specifically designed for their analysis. In this case, it will be used in a context of "inverted class" in which the theoretical concepts will be reviewed by the students independently prior to the lecture session, in which there will be an activity to evaluate their understanding. |
| Objective test | Individual written exam of the theoretical part of the course. |
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