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| Detailinformationen |
| Quellcurriculum |
Bachelorstudium Artificial Intelligence 2021W |
| Ziele |
(*)Students learn to understand the theory and the correct application of advanced topics in computational statistics as well as to independently implement and apply selected methods.
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| Lehrinhalte |
(*)Computer arithmetic, methods of non-linear optimization and root finding, EM algorithm, pseudorandom number generation, numerical integration, Jackknife and bootstrap, permutation tests, regression, precision of statistical computation.
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| Beurteilungskriterien |
(*)Exam, Project
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| Lehrmethoden |
(*)Lecture by instructor; Discussion of the projects, where the solution is presented by the students in a project report; Independent development and application of computational statistical methods
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| Abhaltungssprache |
Englisch |
| Literatur |
(*)Slides. Supplementary reading (books, articles) will be announced each semester.
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| Lehrinhalte wechselnd? |
Nein |
| Äquivalenzen |
(*)in combination with 536DASCICSU21: UE Introduction to Computational Statistics (1.5 ECTS) equivalent to 951STCOCSTK14 KV Computational Statistics (4 ECTS)
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