|Study location||Germany, Berlin|
|Nominal duration||4 weeks (6 ECTS)|
|Tuition fee||€920 per programme
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.
|Registration fee||€60 one-time
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
Although this course is an introductory course, some basic/ general knowledge of programming is recommended.
The entry qualification documents are accepted in the following languages: English / German.
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 python programming course provides participants with a solid understanding of basic python programming and some useful python modules, used mainly for data processing.
The course is comprised of two main components: python programming and advanced python modules. As part of the first component, you will learn about python programming including data types, control structures (if-else; for-loop; while) and basic algorithms; file operations; code-reuse (function, class, module) and program debugging. In the second component, you will learn to use some of the most common and popular python modules for data processing, namely: NumPy, Pandas for data analysis, Matplotlib, Seaborn for data visualization, Requests, and Beautiful Soup for crawling.
This course also addresses python for scientific calculation (using module SciPy) and some basic machine learning methods achieved when learning basic algorithms, e.g. k-means clustering, random forest.
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.