Data Engineering, Master of Science

On-campus program @ Constructor University 

👉 The Master's programme in Data Engineering at Constructor University prepares students for the challenges of today's data-driven world. With a strong focus on the application of computer skills and mathematical knowledge to solve real-world problems, the programme offers specialized tracks in computer, geo, and bioinformatics, as well as business & supply chain engineering. It is suitable for students with different career goals and academic backgrounds, enabling them to work in various industries or to continue their academic career towards a PhD.

At a Glance

🏫 Provider Constructor University, University based in Bremen (Germany)
The Constructor University is a private, state-recognized university in Bremen. It offers study programs in the fields of engineering, natural sciences, humanities, and social sciences, awarding bachelor's, master's, and (in cooperation) Ph.D. degrees. The university was founded in 2001 and has been operating under its current name since 2022. In addition to its international focus and high research activities, the university provides extensive support for students through scholarships and preparatory programs.
🎓 Field of Study Information SciencesData Science & AI
📜 Degree Master of Science (M.Sc.)
⏳ Duration 4 Semesters
🎯 ECTS 120 Credit Points
🌍 Language of Instruction English
📖 Course contents Big Data Challenge, Data Analytics, Computer Science Track, Geo-Informatics Track, Bio-Informatics Track, Business & Supply Chain Engineering Track, Intro to Data Management With Python, Current Topics in Data Engineering, Language, Communication and Presentation Skills, Data-Security & P., IT-Law, Machine Learning, Methods, Data Engineering Advanced Project I, Language, Academic Writing Skills, Data Acquisition Technologies and Sensor Networks, Data Visualization and Image Processing, Methods, Data Engineering Advanced Project II, Language, Ethics and the Information Revolution, Masters Thesis
📚 Electives Computer Science, Geo-Informatics, Bio-Informatics, Business & Supply Chain Engineering
📍 Location Bremen
📅 Enrollment Winter semester
💶 Fees
from 10000 € Semester fee
from 40000 € total
🔗 More Info https://constructor.university

Admission requirements

Applicants should have a Bachelor's degree in a relevant area such as Computer Science, Physics, Applied Mathematics, Statistics, Electrical Engineering, or Telecommunications. They are expected to deepen their knowledge and continue into research-oriented work to obtain a Master's or eventually a Doctorate.

Prospective students must be able to demonstrate a GPA-based scholarship. Possible study financing will be provided individually. The application deadline is 31st July 2024.

Details

The Data Engineering study programme is designed for students who wish to deepen their knowledge in the field of data technology. At the core of the programme is the acquisition of large amounts of data and extracting insights from them. It is embedded in the 'Mobility' focus at Constructor University, which examines the mobility of both individuals and goods, as well as information. Nevertheless, the programme also provides support in other research areas such as health and diversity.

Four specialized tracks allow for a deeper understanding of the subject according to students' career plans and interests. The available tracks are: Computer Science, Geo-Informatics, Bioinformatics, and Business & Supply Chain Engineering. These tracks serve as preparation for advanced projects and the Master's thesis.

The programme is two years long and imparts highly practical knowledge essential for work in the rapidly growing field of data technology. The modular structure is divided into different areas such as Core, Elective, Methods, Discovery, Career, and the Master's thesis, all aimed at achieving 120 ECTS credits.

Graduates typically find employment in industries such as finance, automotive, healthcare, retail, and telecommunications. A Master's degree in Data Engineering also opens up opportunities for transitioning to an academic career, up to a Ph.D.

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