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Teaching GuideTerm Faculty of Computer Science |
| Máster Universitario en Intelixencia Artificial |
 Subjects |
| Process Mining |
| Learning aims |
| Identifying Data | 2022/23 | |||||||||||||
| Subject | Process Mining | Code | 614544025 | |||||||||||
| 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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| Learning outcomes | Study programme competences | ||
| Know the main process discovery techniques and be able to select the most appropriate for a given domain. | AC7 AC13 AC14 AC16 AC28 |
BC7 BC9 |
CC5 CC9 |
| Know how to apply search and optimization techniques to verify the conformity of a process. | AC15 AC29 AC30 |
BC9 |
CC8 |
| Know and develop solutions based on artificial intelligence for predictive monitoring. | AC9 AC11 AC16 |
BC4 BC7 BC10 |
CC9 |
| Understand and solve optimization problems in business processes. | AC21 |
BC5 BC9 |
CC9 |
| Know and understand the quality metrics of a process. | AC11 AC22 |
BC6 |
CC5 |
| Know the main problems that process mining solves. | AC8 AC19 AC20 AC27 |
BC1 BC2 BC6 BC7 BC10 |
CC5 CC8 |
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