Big data has turned out to have giant potential, but poses major challenges at the same time. On the one hand, big data is driving the next stage of technological innovation and scientific discovery. Accordingly, big data has been called the “gold” of the digital revolution and the information age. On the other hand, the global volume of data is growing at a pace which seems to be hard to control. In this light, it has been noted that we are “drowning in a sea of data”.
Faced with these prospects and risks, the world requires a new generation of data specialists. Data engineering is an emerging profession concerned with big data approaches to data acquisition, data management and data analysis. Providing you with up-to-date knowledge and cutting-edge computational tools, data engineering has everything that it takes to master the era of big data.
MSc Graduate Program
Program Structure and Content
The Data Engineering program offers a fascinating and profound insight into the foundations, methods and technologies of big data. Students take a tailor-made curriculum comprising lectures, tutorials, laboratory trainings and hands-on projects. In a unique setting, students also team up with industry professionals in selected courses. The program is composed of six modules over four semesters (two years).
1. CORE-FDE - Foundations of Data Engineering (20 ECTS credit points)
This module introduces the fundamental concepts, methods and technologies of data engineering. Included courses:
- The Big Data Challenge: Topics, Applications, Perspectives
- Big Data Bases and Cloud Services
- Principles of Statistical Modeling
- Data Analytics
2. CORE-ERC - Electives and Remedial Courses (15 ECTS credit points)
This module allows students to either make up for missing academic prerequisites or to strengthen their knowledge in selected application areas of data engineering.
3. CORE-AMA - Advanced Methods and Applications (20 ECTS credit points)
This module covers advanced concepts, methods and technologies of data engineering with a view towards industrial applications. The components of this modules range from semester-long courses to application-driven problem-solving workshops. Typical courses include:
- Semantic Web and Internet of Things
- Document Analysis
- Machine Learning
- Data Acquisition Technologies
- Big Data Management
- Data Visualization and Image Processing
- Statistical Modeling and Predictive Analytics
- Internet Security and Privacy
4. CAREER-SL - Skills and Languages: (15 ECTS credit points)
In this module, students acquire skills preparing them for a career as data engineers in industry. Included courses:
- Data Ethics
- Legal Foundations of Data Engineering
- Language Courses
- Further skills courses
5. RESEARCH-IRP - Industry and Research Projects (20 ECTS credit points)
This module features two advanced projects in close collaboration with Jacobs University faculty and partner companies.
- Advanced Project I
- Advanced Project II
6. RESEARCH-MT - Master’s Thesis (30 ECTS credit points)
In the fourth semester, students conduct research and write a master’s thesis guided and supported by their academic supervisor.
For more details on the curriculum please download the program handbook below.