Graduates of the master’s program earn an invaluable professional qualification. They are able to take on leadership or management positions, particularly where the design, building, maintenance, and operation of complex information systems play a key role. Upon graduation students are ready to assume the position of data engineer, data scientist, data specialist or strategic data analyst.  

The Master of Science in Data Engineering is a four-semester program at the Faculty of Digital Engineering, a faculty jointly founded by the Hasso Plattner Institute (HPI) and the University of Potsdam (UP).

In their studies, students deepen the scientific foundations of computer science and acquire theoretical, methodical and practical skills to deal with complex information systems. The focus thereby is on the core areas of data management, data analysis, and data visualization. Focused on actual problems from industry and research, students learn to map the real process of a data-driven project.

Besides receiving in-depth knowledge of IT technology, students achieve competency in so-called soft skills, which play a vital role in the successful management of large IT projects. 

The master’s program has a flexible and individualized structure. Students can choose from a wide range of subjects and tailor the program to fit their individual needs and career goals.

An overview of all modules of the master's program Data Engineering can be found here. (Geman only)

Compulsory Modules

• DE-A Module Data Analysis
  This module shows the limits of fundamental data analysis methods and teaches in-depth methods and concepts of different data analysis paradigms in the areas of supervised learning, unsupervised learning, statistical data analysis, as well as interactive data exploration.
• DE-S Module Big Data Systems
  Big data systems master the acquisition, processing and storage of data through new technologies for extensive data (volume) from heterogeneous sources (variety) with a high acquisition frequency and a fast processing time (velocity).
• DE-M Module Data Management
  This module teaches the architectures and methods for the distributed parallel processing of data as established concepts for the mastery of big data. Moreover, it provides fundamental contents on data management tasks such as data collection, data preparation, data transformation and data validation.
• DE-V Module Data Visualization
  In this module, the tasks and goals in the field of information visualization are defined and the concepts and methods of visualization conveyed. These include graphical primitives, visual variables, and dimensions of visualization and presentation forms for information.
• DE-EG Module Ethics and Society
  This module addresses ethical questions, for example the relationship of state to citizen and of company to citizen, particularly under the aspect of modern data processing. The objective is to be able to ethically evaluate conflict situations in business and society and to preventively avoid such situations.
• DE-RWM Module Law Economics and Management
  This module teaches legal and economic issues that are relevant in the creation and distribution of software products and the founding and management of IT companies. Key topic areas are intellectual property rights, software contract law as well as software licensing law.
• DE-L Module Data Engineering Lab
  In the data engineering lab, a team of students work on a selected, research-oriented question related to big data systems from one of the Hasso Plattner Institute’s Research Groups. The question is analyzed and then for a sub-area a solution is designed, constructively implemented and scientifically documented.

 Specialization Areas

• Data Analytics
• Data Preparation
• Data Security
• Scalable Data Systems
• Complex Data Systems

Soft Skills

• Communication
• Management and Leadership
• Design Thinking Basic Track 
• Design Thinking Advanced Track

Master Project