|
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.
|
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.
|
Beurteilungskriterien |
(*)Exam, Project
|
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
|
Abhaltungssprache |
Englisch |
Literatur |
(*)Slides. Supplementary reading (books, articles) will be announced each semester.
|
Lehrinhalte wechselnd? |
Nein |
Äquivalenzen |
(*)in combination with 536DASCICSU21: UE Introduction to Computational Statistics (1.5 ECTS) equivalent to 951STCOCSTK14 KV Computational Statistics (4 ECTS)
|
|