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| Detailinformationen |
| Quellcurriculum |
Bachelorstudium Transformation Studies. Art x Science 2024W |
| Ziele |
(*)Discussing a series of historical examples of transformation processes, students will understand (a) what are the basic capabilities of computer systems, (b) what are the strengths and limitations of addressing a task with classic algorithms, and (c) what are the strengths, limitations and risks of using machine learning and AI instead. Students can differentiate classic and AI approaches and judge the relevance of either for specific future transformation processes.
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| Lehrinhalte |
(*)Basics of Von Neumann architecture, imperative programming,
databases, networking; basics of regression, classification, neural
networks, deep learning
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| Beurteilungskriterien |
(*)Combined assessment of homework and a final exam
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| Lehrmethoden |
(*)Slide presentations and live discussions
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| Abhaltungssprache |
Englisch |
| Literatur |
(*)Electronic course material provided for download
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| Lehrinhalte wechselnd? |
Nein |
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