Erklärbare und sichere KI
Summer
(engl. Explainable and safe AI )
Modulnummer: FIN-INF-110496 |
| Link zum LSF: | LSF |
| Verantwortung: | Sebastian Stober |
| Dozent:in: | Sebastian Stober |
| Lehrveranstaltungen: |
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| Verwendbarkeit: | - B.Sc. INF: Informatik - Wahlpflicht - B.Sc. INF: Studienprofil: Künstliche Intelligenz - B.Sc. CV: Informatik - Wahlpflicht - B.Sc. INGINF: Informatik - Wahlpflicht - B.Sc. WIF: Gestalten und Anwenden - Wahlpflicht - B.Sc. INF (bilingual): Informatik - Wahlpflicht |
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Kürzel XAI |
CP 5 |
Semester Summer |
Fachsem. ab 3. |
Dauer 1 Semester |
Sprache deutsch |
Niveau Bachelor |
Angestrebte Lernergebnisse:
The students ...
- can confidently apply methods to explain decisions and internal representations, as well as processes of machine learning models
- have the ability to assess the quality of models beyond accuracy metrics
- can improve models in a targeted manner
Inhalt:
Classification of different categories of explainability methods for machine learning models and requirements for user-centered explanations. Presentation of directly interpretable models (ante-hoc) as well as analysis and visualization methods for black box models (post-hoc). In addition, basic post-hoc explanation techniques with model-agnostic and model-specific approaches are presented.
Arbeitsaufwand:
- 56h attendance time (lecture + exercise)
- 94h independent work (preparation and post-processing of lecture (OER) and exercise, working on exercise and programming tasks)
| Prüfungsvorleistungen: | Studien-/Prüfungsleistungen: | Lehrform / SWS: |
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Written exam 120 minutes
Announcement of the necessary preliminary work in the first week of the course.
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| Voraussetzungen nach Prüfungsordnung: | Empfohlene Voraussetzungen: |
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none
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Deep Learning for Engineers
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| Medienformen: | Literatur: |
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