The course will be online. With confirming your participation we will send you a Zoom-Link to join the course.
For students the participation is for free. For employees we charge a participation fee of 200€.
You already have some knowledge about Machine Learning (ideally you followed one of our previous courses) and are interested in learning more about Natural Language Processing. Particularly in this course you should be dmotivate to bring your own contribution – it's a great opportunity to learn and discuss latest discoveries in the field.
This course is based on the Coursera Specialization on Natural Language Processing (https://www.coursera.org/specializations/natural-language-processing).
The course will provide you with knowledge and experience about most recent and advanced machine learning models for natural language processing. You will be able to train and use neural network to provide auto-correction suggestion, complete sentences and even build a chatbot.
You will then apply the newly acquired knowledge to implement your own machine learning project in a team.
How it works
The course will take place every Thursday from 4 pm to 5:45 pm.
Before the first meeting there will be a semesterkick-off.
During the current Coronavirus outbreak, the course will also be available online via Zoom.
During the week you will be expected to work through the assigned online course content, which will take you between 4 to 5 hours each week, open questions considering the course content and possible additional implications will then be discussed in the weekly offline course on Monday. Towards the end of the semester you will then work in a team on your own machine learning project.
All needed software and online course content is free. For the practical assignments in the online course, however, it will be necessary to create a Google account.
In order to receive a certificate of attendance for this course, active participation is expected, and no more than two classes may be missed. The active participation is proven by screenshots of your taken online courses, the final presentation of your project by you and your team, and the delivery of a documented project source code.
The same conditions also apply in order to receive credit points.
Further details may be given in the course and here.