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Teaching GuideTerm Faculty of Computer Science |
| Máster Universitario en Intelixencia Artificial |
 Subjects |
| AI Project Management |
| Learning aims |
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| Identifying Data | 2022/23 | |||||||||||||
| Subject | AI Project Management | Code | 614544021 | |||||||||||
| Study programme |
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| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Official Master's Degree | 2nd four-month period |
First | Obligatory | 3 | ||||||||||
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| Learning outcomes | Study programme competences | ||
| Know, understand and analyze the life cycle, the existing models and methodologies within the field of artificial intelligence that allow the design and implementation of reliable and efficient planning for the development of intelligent systems | AC20 AC21 AC29 |
BC1 BC2 BC4 BC5 BC6 BC7 BC9 |
CC9 |
| Know the possibilities of public and private funding for research activities in the field of innovative and frontier technologies | AC19 AC20 AC22 AC28 AC29 |
BC1 BC4 BC5 BC6 BC7 BC9 BC10 |
CC5 CC8 |
| Know and analyze real applications of software engineering methodologies and techniques applied to AI. Know how to use techniques and tools to support the planning and management of projects and risks | AC20 AC21 AC28 AC29 |
BC2 BC4 BC5 BC6 BC7 BC9 |
CC9 |
| Be able to propose a complete plan for an R&D project in AI and know the mechanisms for managing and internationalizing the results | AC19 AC20 AC21 AC22 AC28 AC29 |
BC1 BC2 BC4 BC5 BC6 BC7 BC9 BC10 |
CC5 CC8 CC9 |
| Know the implications of movements such as Open Access, Science and Data and the benefits of facilitating the participation of society in science and innovation (RRI) | AC19 AC20 AC21 AC22 AC28 AC29 |
BC1 BC2 BC4 BC5 BC6 BC7 BC9 BC10 |
CC5 CC8 CC9 |
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