Our courses are open to all and free of charge for students, pupils, trainees, founders, scientific staff, job seekers, refugees, and pensioners. For employees and self-employed persons, a fee of 200 euros is charged when acquiring a certificate of achievement. Employees and self-employed persons can apply for a scholarship via firstname.lastname@example.org.
The course instruction is hybrid, which means you can participate either online via Zoom or in person in Kiel (see location listed in the dates). If you participate online, it is expected that you turn on your camera and have a sufficient internet connection.
In this course you will, at first, get a very general, rather non-technical introduction into transformer models and the possibilities to apply them. Thereafter, you will learn how to apply transformer models yourself by using the Hugging Face library. In the remaining part of the course, we will then discuss different transformer models and their application in more detail.
As in all our machine learning courses, a main focus of this course will be the completion of your own NLP project that all course participants will have to conduct. You are free to bring your own ideas or data sets for the project.
All needed software and online course content is free.
This course is part of the opencampus.sh Machine Learning Degree. Participants of the program for the Machine Learning Degree get preferred access to this course. Find more information on the opencampus.sh Machine Learning Degree here.
You already have some programming knowledge and basic knowledge of neural nets and machine learning algorithms.
In order to receive a certificate of achievement ("Leistungszertifikat"/ ECTS) for this course, active participation is expected, no more than two classes may be missed, and you have to conduct a practice project in a team of 2 to 4 persons. At the end of the course the project has to be presented and a well documented project source code has to be submitted.
Before the first course meeting there will be a Course Kick-Off Event on October 21.
In the Kick-Off you will meet your course instructor, can ask questions about the participation in the course, and get helpful information to prepare for the start of the course. The attendance at the Kick-Off is not mandatory but recommended for all participants.