Classes
Doctoral Students
Intenships
Thesis, Project, Seminar
Classes
Engineering with Gen AI
A hands-on class on how to build with generative AI.
With guest lectures and technical support from Amazon Web Services, we explore technical, scientific, practical, and ethical questions that come with a new AI wave
Practical ML and NLP
This hands-on course blends the foundations of machine learning with advanced natural language processing, giving you the skills to build, train, and deploy models using Amazon SageMaker and other AWS services.
Statistical Machine Learning
The course provides a statistical perspective on machine learning, contrasting frequentist and Bayesian approaches. It covers fundamental concepts, including Maximum Likelihood (ML) and Maximum a Posteriori (MAP) methods, as well as model averaging and fully Bayesian techniques.
Delivered in collaboration with Prof. Marius Kloft.
Thesis, Projects, and Seminars
Finding the right literature and prior art is a crucial skill for data science work in and out of academia.
We give exciting, current topics to our students to review over the course of a semester. Students who do well are usually offered a research assistant position in our group to continue their work.
Our thesis and guided project students work alongside our team, usually mentored by one of our senior researchers, to tackle a real-world problem.
By doing a guided project with us, you will contribute to something substantial while obtaining end-to-end data science skills and expanding your portfolio to prepare for a career after graduation.
Doctoral Students
There are two ways of pursuing a doctorate with us:
- Full-time
- Alongside working (at DFKI or elsewhere)
Our full-time students receive a stipend to support their studies. We offer opportunities to our research staff at DFKI to earn a doctorate alongside their work.
Research Internship
Interning at our department is a great way to learn more about applied research, be immersed in our lively and dynamic culture, and learn by doing and testing yourself in a research role.
Some of our current full-time staff and doctoral students started out by doing a research internship with us— think of it as a prolonged “get to know one another” period where you can see how things are without committing long-term.
We welcome interns at all stages of their academic career— bachelors, masters, or doctoral students— and are happy to support thesis work during the internship.