Education and Career Paths
BIFOLD Curriculum
BIFOLD offers students a wide range of opportunities to learn, grow, and develop their skills. The training program addresses the emerging challenges and requirements posed by the rapid deployment of AI in diverse areas, including the natural sciences, healthcare, medicine, humanities, and industry. Given the diverse set of skills required of scientists today, graduates need dual expertise and training in both Data Management (DM) and Machine Learning (ML); so that upon graduation, they will possess technical skills to address the pressing problems of today and be well prepared to face tomorrow’s grand challenges.
This website provides an overview of BIFOLD's educational program. Besides the foundational/theoretical courses in DM and ML, further courses offer knowledge in subject-specific methods and approaches pertinent to the field of DM and ML, their intersection, and their applications. Students will gain the required theoretical knowledge in data analysis methods, their application to real-world problems, and further develop their programming skills with a focus on both data-processing systems and machine learning.
All students are in addition welcome to join the BIFOLD Colloquia. These lectures offer insights into the latest research conducted by BIFOLD scientists and international guest speakers from academia and industry.
This website is currently under construction and represents only a selection of BIFOLD's course offers.
Data Systems & Information Management
Welcome to the Data Systems Lab
The Big Data Engineering (DAMS) Group and the Database Systems and Information Management (DIMA) Group at TU Berlin offer numerous opportunities for you to learn, grow, and develop. Incidentally, DAMS and DIMA are members of the Data Systems Lab (DASL) in BIFOLD. Together they developed a poster to inform about their educational programs, course offerings, thesis opportunities, and prospective career paths. It is particularly informative for those interested in pursuing a Master’s or PhD with a concentration in data management, big data engineering or technologies and systems for data science.
Machine Learning
The Machine Learning Group is chaired by Prof. Dr. Klaus-Robert Müller and focuses on methodological and theoretical improvements as well as applications in machine learning.
ML courses
Machine Learning and Security
The Machine Learning and Security Group offers a number of courses each semester that revolve around machine learning and security. These include lectures on learning algorithms in security systems and adversarial machine learning as well as labs where people can experiment with attacks and malicious code.
Big Data Analytics in Earth Observation
The Big Data Analytics for Earth Observation Group offers a number of courses each semester that revolve around Remote Sensing and Big Data.