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.
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BIFOLD Courses or Master Track
BIFOLD Courses
Data Systems & Information Management
Welcome to the Data Systems Lab
The Big Data Analytics for Earth Observation (BigEarth) Group, the Data Integration und Data Preparation (D2IP) Group, the Big Data Engineering (DAMS) Group, the Data Engineering for ML (DEEM) Group and the Database Systems and Information Management (DIMA) Group at TU Berlin offer numerous opportunities for you to learn, grow, and develop. Incidentally, BigEarth, D2IP, DAMS, DEEM and DIMA are members of the Data Systems Lab (DASL) in BIFOLD. Together they developed a poster to inform about our 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.
Data Science and Engineering Master’s Track
School IV, Electrical Engineering and Computer Science, of Technische Universität Berlin offers a Data Science and Engineering Track (Certification) integrated in the master’s study program of Computer Science, Computer Engineering and Information Systems Management. During the studies three columns support the specialization:
- Data Analytics
- Scalable Data Management
- An Application Area
Examples of application areas include: medical science, materials research, energy, and logistics.
A wide range of English courses guarantees that students without German language knowledge can follow this track.
A description of the track may be found here: Data Science and Engineering Track [PDF]
Learn more about the Data Analytics Laboratory.