Inhalt des Dokuments
In this course students will learn how read, write and execute fast and efficient codes, especially for machine learning algorithms in Python.
Learning Goals and Syllabus
Students will learn:
- Understanding the concepts of scientific programming
- Scientific plotting
- Writing fast and efficient code
- Executing and benchmarking
Reading week: June 28th - July 2nd, 2021. Flexible, 5 hours preparatory work to be done on-demand.
Online course: July 5th - July 16th, 2021. Estimated session times are Mondays through Fridays for live lectures and group sessions, etc.
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 firstname.lastname@example.org 
Please note this is a full-time, intensive course. Weeks 1 and 2
will involve approximately 30 hours of workload.
A detailed syllabus with information on the schedule will be made available to registered participants.
You may find the syllabus useful when discussing with your home university whether the ECTS credits attainable for this course are accepted by them.
For all students interested in machine learning and willing to learn how to implement the algorithms properly using most recent programming concepts from Python language.
Prerequisites and Technical Requirements
Participants of the TU Berlin Summer & & Winter University must meet the following requirements: (i) B2 level English, or equivalent and (ii) at least one year of university experience. Working professionals are also welcome to take part in the program.
Basic programming knowledge is recommended. Be aware that lack of such skill will increase the time demand of the class.
We will ask participants to fulfill the following technical requirements:
- Fully functional device (laptop, tablet, PC)
- Stable internet connection
- Software: Zoom (App installed on desktop or over browser. Participants are requested to use their real name as zoom account name)
- Recommended: external headset for better sound quality
- Most recent version of any Web browser ( e.g. Chrome, Firefox, Safari )
Sergej Dogadov is a teaching assistant at TU Berlin in the department for intelligent data analysis and machine learning with more then five years of teaching experience.
He holds B.S. and M.S. degrees in computer science from the TU Berlin with the main focus in intelligent systems and theoretical informatics.
Current research interests are Bayesian methods, probabilistic neural networks, explainable AI and joint energy models.
Course fees for Python Programming for Machine Learning are as follows:
Student: 720 Euro
Working professional/Non-student: 1120 Euro
The early bird discount is available for all participants until April 1st 2021.
Please note that students will be required to upload proof of their student status (student card/ enrollment information) during the registration process.