Bootcamp – introduction to mathematics
General data
Course ID: | 1000-317bBIM |
Erasmus code / ISCED: |
11.3
|
Course title: | Bootcamp – introduction to mathematics |
Name in Polish: | Obóz wstępny – wprowadzenie do matematyki |
Organizational unit: | Faculty of Mathematics, Informatics, and Mechanics |
Course groups: |
Obligatory courses for 1st year Machine Learning |
ECTS credit allocation (and other scores): |
3.00
|
Language: | English |
Type of course: | elective monographs |
Short description: |
The goal of the course is to present the set of common mathematical notions necessary to understand contemporary techniques of machine learning as well as to instil the mathematical apparatus necessary to efficiently use them. |
Full description: |
The lecture has the form of an intensive course taught during the first two weeks of the first semester. The topics are divided into three thematic groups: * Linear algebra and geometry (2 lectures) + SVD decomposition + Other matrix decompositions + Structure theorems * Calculus (2 lectures) + Chain rule + Multivariate integrals * Probability theory and statistics (3 lectures) + Random variables, mean, variance, higher moments + Central Limit Theorem + Typical probability distributions |
Bibliography: |
1. A. Białynicki-Birula, Algebra liniowa z geometrią, Państwowe Wydawnictwo Naukowe, Biblioteka Matematyczna t.48, Warszawa 1979. 2. Zbiór zadań z algebry , pod red. A. I. Kostrikina, wydanie drugie zmienione, Wydawnictwo Naukowe PWN, 2005-2013 3. T. Koźniewski, Wykłady z algebry liniowej I i II , Uniwersytet Warszawski, 2004, 2006 4. Kazimierz Kuratowski, Rachunek różniczkowy i całkowy. Funkcje jednej zmiennej, PWN. 5. W. Kołodziej, Analiza matematyczna, PWN, Warszawa 2009. 6. A. Birkholc, Analiza matematyczna: Funkcje wielu zmiennych. Wydanie II, PWN, Warszawa 2018. 7. G. M. Fichtenholz, Rachunek różniczkowy i całkowy. Tom 1-3, PWN, Warszawa 2007. 8. W. Rudin, Podstawy analizy matematycznej, PWN, Warszawa 2009. 9. W. Rudin, Analiza rzeczywista i zespolona, PWN, Warszawa 2009. 10. P. Strzelecki, Analiza matematyczna II (skrypt wykładu), http://dydmat.mimuw.edu.pl/sites/default/files/wyklady/analiza-matamatyczna-ii.pdf 11. J. Jakubowski, R. Sztencel, Rachunek prawdopodobieństwa dla prawie każdego, Script, Warszawa 2006. 12. W. Krysicki i współautorzy, Rachunek prawdopodobieństwa i statystyka matematyczna w zadaniach , część I, II, Wydawnictwo Naukowe PWN, Warszawa 2004. 13. W. Feller, Wstęp do rachunku prawdopodobieństwa , Wydawnictwo Naukowe PWN, Warszawa 2006. (dla chętnych) |
Learning outcomes: |
Knowledge: the student * has in-depth understanding of the branches of mathematics necessary to study machine learning (probability theory, statistics, multivariable calculus, and linear algebra) [K_W05] Abilities: the student is able to * construct mathematical reasoning [K_U06]; * express problems in the language of mathematics [K_U07]. Social competences: the student is ready to * critically evaluate acquired knowledge and information [K_K01]; * recognize the significance of knowledge in solving cognitive and practical problems and the importance of consulting experts when difficulties arise in finding a self-devised solution [K_K02] |
Assessment methods and assessment criteria: |
Mid-term/end-term test |
Classes in period "Winter semester 2024/25" (past)
Time span: | 2024-10-01 - 2025-01-26 |
Go to timetable
MO WYK
CW
CW
TU WYK
CW
CW
W WYK
CW
CW
TH WYK
WYK
CW
CW
CW
CW
FR CW
CW
|
Type of class: |
Classes, 15 hours
Lecture, 15 hours
|
|
Coordinators: | Andrzej Nagórko | |
Group instructors: | Gracjan Góral, Andrzej Nagórko, Mateusz Wyszyński | |
Students list: | (inaccessible to you) | |
Credit: | Examination |
Classes in period "Winter semester 2025/26" (future)
Time span: | 2025-10-01 - 2026-01-25 |
Go to timetable
MO WYK
CW
CW
TU WYK
CW
CW
W TH WYK
CW
CW
FR WYK
CW
CW
|
Type of class: |
Classes, 15 hours
Lecture, 15 hours
|
|
Coordinators: | Andrzej Nagórko | |
Group instructors: | Kamil Ciebiera, Andrzej Nagórko, Mateusz Wyszyński | |
Students list: | (inaccessible to you) | |
Credit: |
Course -
Examination
Lecture - Examination |
Copyright by University of Warsaw.