The lecture Mathematical Introduction to Machine Learning held by Dr. rer.-nat. Igor Bjelakovic will start this semester on Wednesday, 15th of October 2025. The course takes place as presence lecture every Wednesday from 12:00 - 14:00 (c.t.) in the HFT- TA Building/ room: 131. The last lecture will be on 11th of February 2026.
In order to complete the first module (Mathematics of Machine Learning), the lecture Theory and Algorithms of Machine Learning for Communication has to be taken additionally in the summer semester term (held by Prof. Dr.-Ing. Slawomir Stanczak).
In order to complete the second module (Modern Signal Processing for Communications), the lecture Modern Signal Processing for Communications has to be taken additionally in the summer semester term (held by Dr.-Ing. Renato L.G. Cavalcante).
After completing both lectures you will be tested in one oral exam and will receive 6 credit points. Please ask for an examination date at sekretariat@netit.tu-berlin.de.
Information for exchange students: it is possible to be examined only in one lecture of the module with 3 Credit Points. You do not need to register at the Examination Office, simply ask for an examination date at sekretariat@netit.tu-berlin.de. After passing the exam you receive a certificate.
Please provide the following information in the e-mail for the exam registration:
- Matriculation number & degree program
- Exchange student (yes/ no)
- Should the examinations take place in two parts or one examination?
Recommended Literature
- S. Shalev-Schwartz and S. Ben-David: "Understanding Machine Learning: From Theory to Algorithms", Cambridge University Press, 2014
- M. Mohri, A. Rostamizadeh, A. Talwalker. “Foundations of Machine Learning”, MIT Press, 2018
- R. Vershynin, “High-Dimensional Probability: An Introduction with Applications in Data Science”, Cambridge University Press, 2018
- M. Wainwright, “High-Dimensional Statistics: A Non-Asymptotic Viewpoint”, Cambridge University Press, 2019
- P. Rigollet: Mathematics of Machine Learning, MIT (https://ocw.mit.edu/courses/mathematics/18-657-mathematics-of-machine-learning-fall-2015/lecture-notes/)
- John C. Duchi, "Introductory Lectures on Stochastic Optimization", Stanford University (https://web.stanford.edu/~jduchi/PCMIConvex/Duchi16.pdf)
- Trainer/in: Igor Bjelakovic
- Trainer/in: Kerstin Reinhardt
- Trainer/in: Ine Scharse