|Nominale Dauer||4 weeks (6 ECTS)|
|Studiengebühren||920 € pro Programm
The program price consists of the course/tuition fee (student or working professional, see details below) plus the registration fee (€60).
Student course/tuition fee: €920
This course/tuition fee covers the online course, course materials and a digital cultural program.
|Anmeldegebühr||60 € einmalig
The registration fee is in addition to the course/tuition fee and covers the processing of your application. It is payable upon registration. Please note that the registration fee is non-refundable.
At least one year of university experience or equivalent work experience
Participants from all fields and disciplines are welcome.
- Linear algebra
Die Zulassungsunterlagen werden in folgenden Sprachen akzeptiert: Englisch / Deutsch.
Please upload one of the following documents:
Upload copies in a word or pdf format
All applicants are required to upload a document or certificate to demonstrate their proficiency in English language. If you are a non-native English speaker, you must prove you have a score equivalent to the level B2 or above in the European system (the Common European Framework of Reference for Languages, or CEFR), or provide evidence that you have undertaken an equivalent degree/studies in English.
More details: www.tu-berlin.de/menue/summer_university/requirements/
If you are a native English speaker, please select this during registration. You will then be exempt from having to upload proof of English level.
This course will focus on Data Science with Python, starting with the basic of Python programming and machine learning algorithms to solving arbitrary complex models using graphical Bayesian modelling and sampling.
Reading week: January 3rd – 7th, 2022. Flexible, 20 hours preparatory work to be done on-demand.
Online course: January 10th – 28th, 2022. Estimated session times are Mondays through Fridays from 9 am to 2 pm CET for live lectures and group sessions.
Please note that exact session times will be confirmed once registrations have closed (sessions will be scheduled according to the time zones of the registered course participants).
Should you have any questions regarding the course timetable, please contact us at email@example.com
Please note this is a full-time, intensive course and participants will be expected to attend lectures and/or complete independent study Monday through Friday. Additional study may also be required on weekends.