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Study at Constructor University

Bremen, Germany

Data Engineering
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Data Engineering

Master of Science at Constructor University

Programme details
Degree: Master of Science (MSc)
Disciplines: Data Science & Big Data
Computer Science
Duration: 24 months
ECTS points: 120
Study modes: full-time
University website: Data Engineering
Annual tuition (EEA) 20,000 EUR
Annual tuition (non-EEA) 20,000 EUR

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Description:

The graduate program in Data Engineering offers a fascinating and profound insight into the methods and technologies of this rapidly growing area. The program combines big data aspects of "Data Analytics" as well as of "Data Science" with the technological challenges of data acquisition, curation, and management. Thus, the program provides the essentials for paving the way to a successful career: computer skills and mathematical understanding paired with practical experience in selected application fields. The Data Engineering program attracts students with diverse career goals, backgrounds, and prior work experience. Therefore, the program offers four focus tracks within which the students can choose to specialize further: Computer Science, Geo-Informatics, Bio-Informatics, and Business & Supply Chain Engineering. These tracks are a preparation for the Advanced Projects within the Discovery Area and the Master Thesis.

Career Perspectives:

Demand for Data Engineers is massive. Typical fields of work encompass the finance sector, the automotive and health industry as well as retail and telecommunications.

Today we are "drowning in data and starving for information" while acknowledging that "data is the new gold". However, deriving value from all the data now available requires a transformation in data analysis, in how we see, maintain, share and understand data. Data Engineering is an emerging profession concerned with the task of acquiring large collections of data and extracting insights from them. It is driving the next generation of technological innovation and scientific discovery, which is expected to be strongly data-driven. The program is embedded in the "Mobility" focus area at Jacobs University. This focus area investigates the mobility of people, goods, and information. Even though the Data Engineering program is centered in "Mobility", it includes contributions from and supports applications in the two other research foci: Health (bioactive substances), and Diversity (in modern societies). Four program tracks to allow specialization: Moreover, the Data Engineering program attracts students with diverse career goals, backgrounds, and prior work experience. Therefore, the program offers four focus tracks within which the students can choose to specialize further: Computer Science, Geo-Informatics, Bio-Informatics Business & Supply Chain Engineering. These tracks are a preparation for the Advanced Projects within the Discovery Area and the Master Thesis. Computer Science Track: In particular, Computer Science provides students with the skills to go beyond a mere usage of existing toolboxes and to develop innovative data analysis techniques of their own design. Geo-Informatics Track: It gives students an introduction to Geographic Information System techniques, principles of spatial analysis, and data mining with integration of remote sensing and GPS. It thereby provides an early exposure to earth science data and its handling. Bioinformatics Track and the analysis of biomedical data: Integration and model-based interpretation of high-throughput data are severe bottlenecks in biomedical and pharmaceutical research. Data Engineering prepares students for the novel computational challenges in these fields. Business & Supply Chain Engineering Track: Students can also choose the specialization track in Business & Supply Chain Engineering. A vast amount of data is collected as part of business processes in particular along supply chains. In this specialization track, students will concentrate on the full data analysis cycle including pre-processing of data, data analysis and deployment of model results within the business process.


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