Courses

We offer a variety of courses in the field of data engineering at both Bachelor- and Master level in all curricula of the computer science department.

The Data Engineering group contributes lectures, seminars, projects, and thesis topics to the study programs offered by the department of computer science. Our teaching activities cover the broad area of data management, data engineering, and data science. They are tightly aligned with courses offered by other groups of our department to offer a comprehensive and coherent curriculum with the opportunity to specialize on data-centric topics. 

Courses

Bachelor

  • Introduction to databases - Must reads (seminar, winter term, German). In this seminar, students study papers that have shaped the data management field. Papers are typically selected among those featured in "Readings in Databases" and can be considered as papers that introduce data management solutions that are behind many modern applications. 
  • Datenbanken Evergreens (seminar, summer term, German). This seminar focuses on studying papers and topics that have been recognized as being most influential in the past 5 years. Thus, this seminar gives both a perspective on how the data management field has evolved over time and what novel topics have emerged. Papers that serve as a starting point are typically selected among those awarded a Test-of-Time or Influential Paper award at the major international data management conferences (ACM SIGMOD, VLDB, IEEE ICDE, ...). 
  • Projects and thesis topics. We regularly offer student projects or thesis topics around data engineering topics that relate to current research projects. We invite you to browse our research websites and contact us with your specific interests to see if we can offer you a topic. 

Master

  • Information Integration (lecture, winter term, English). Integrating information consist in combining data gathered from various sources for a specific application need. These data are commonly heterogeneoys, come from autonomous sources, and vary in structure, making information integration a challenging task to be solved automatically. Nevertheless, it is the basis for information exchange, comprehensive search, and many data analytics applications. The goal of this lecture and accompanying practicals is to provide an overview of challenges in information integration, enable the students to assess and apply available approaches and technologies, as well as equip students with the necessary knowledge to customize solutions to specific applications.
  • Data Engineering (lecture, summer term, English). Data engineering involves any data processing necessary to prepare data for subsequent use, e.g., for data analysis. This lecture covers foundations, algorithms, and systems on selected topics of data engineering, with a focus on processing large amounts of semi-structured data as is commonly found on the Web. Throughout this lecture and its practicals, students obtain an overview of the general data engineering process, get detailed knowledge on possible solutions, and learn how to develop data engineering solutions of their own.
  • Advanced Data Engineering (seminar, winter term, English).  This advanced seminar provides students with a deep-dive into recent research contributions on algorithms and systems for data engineering. Typical topics relate back to data acquisition, data integration, data cleaning, metadata management, or system architectures as discussed in the Data Engineering lecture. 
  • Projects and thesis topics. We regularly offer student projects or thesis topics around data engineering topics that relate to current research projects. We invite you to browse our research websites and contact us with your specific interests to see if we can offer you a topic. At master level, we explicitely encourage students to directly contribute to our research, which may lead to joint scientific publications.
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