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Data Engineering

Data Engineering Technologies

Master of Science - Online Graduate Program
Program overview

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. 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.

Our online graduate program in Data Engineering Technologies is taught by the School of Computer Science & Engineering. Students gain a fascinating and profound insight into the methods and technologies of this rapidly growing area. The program combines the big data aspects of “Data Analytics” and “Data Science” with the technological challenges of data acquisition, curation, and management via databases and warehouses, big data pipelines, and cloud computing.

Degree and ECTS points: Master of Science, 120 ECTS

Advantages of studying with us online

Program aims and structure

 

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Target group

The Data Engineering Technologies program is targeted towards students who have completed their BSc in computer science, physics, applied mathematics, statistics, electrical engineering, communications engineering, or related disciplines, and who want to deepen their knowledge with a research-oriented master’s degree or ultimately a PhD.

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Key facts

Duration:
2 years full-time
€ 5,000
Tuition per academic year
Fall Intake 2024:
Classes start the first week of September

Program aims and structure

The program is an online program with optional blended elements, e.g., in summer. Lectures incorporate asynchronous material and primarily follow a flipped classroom model, i.e., including application components in the spirit of problem-based- as well as project-based-learning. Practical components, particularly labs, projects, and thesis are based on remote access and distributed development. Tutoring includes virtual study groups, peer evaluation and mentoring by faculty. Performance evaluations are conducted as online e-exams.

The remote work aspects include collaborative software development and remote access to physical devices for, e.g., control, monitoring and maintenance. Due to the aspects of independent, self-governed knowledge acquisition, the students are prepared for life-long learning, where additional knowledge and skills need to be acquired or updated in a regular fashion, especially in Data Engineering Technologies.

The program aims to provide an in-depth understanding of the essential aspects of data-based decision-making and the skills required to apply and implement these powerful methods in a successful and responsible manner. Apart from the necessary programming skills, this comprises:

  • methods of data acquisition both from the internet and from sensors;
  • methods to efficiently store and access data in large and distributed data bases;
  • statistical model building including a wide range of data mining methods, signal processing, and machine learning techniques;
  • visualization of relevant information;
  • construction and use of confidence intervals, hypothesis testing, and sensitivity analyses; ▪ know the legal foundations of data engineering;
  • methods to ensure data security and privacy;
  • awareness of the societal and ethical implications of digitization;
  • scientific qualification;
  • competence to take up qualified employment in Data Engineering;
  • competence for responsible involvement in society;
  • personal growth.

At the end of the 2-year online program, students will have acquired a strong body of expertise, both in content and in computational skills, to solve challenging problems in digital societies thoughtfully and responsibly. More specifically, graduates of the DSSB (online) program will be able to:

  1. identify, analyze, interpret, and critically assess the social (e.g., business, economic, and political) causes and consequences of the digital transformation of societies.
  2. academically reflect and evaluate the legal and ethical implications surrounding privacy, data sharing, algorithmic decision making, and new business models in various digitalized sectors.
  3. combine data science concepts and put them into practice by developing and designing state-of-the-art applications.
  4. develop scientific and professional solutions for social, ecological, economic, health, scientific, and political problems.
  5. creatively and convincingly solve research implementation problems.
  6. learn programming and implementation in at least one computer language (R or Python) and acquire at least basic skills in the other.
  7. use state-of-the-art digital data mining methods from the Internet and other sources.
  8. efficiently and securely manage social media and business data.
  9. deliberately choose between, adapt, and potentially develop statistical models for “big data”.
  10. elaborately command analytical, critical, and synthesizing quantitative skills to correctly model and interpret scientific results, make valid predictions, and derive thoughtful conclusions and interventions for pressing social and business problems.
  11. apply innovative writing, communication, presentation techniques, and state-of-the-art visualization tools to reach out effectively and convincingly to scientific and non-scientific audiences.
  12. efficiently and effectively use online materials to boost self-learning and time-management skills to sharpen one’s professional expertise and stay updated in a rapidly developing scientific domain.
  13. function very well in an international and diverse working environment.
  14. adhere to and defend ethical, scientific, and professional standards.
  15. make valuable contributions to society and businesses.
  16. grow personally to become a responsible, smart, and resilient researcher, leader, and collaborator.
  17. take up an ambitious academic, business, or professional career in thriving digital domains.

schematic study plan det online

Study program handbook Fall 2024 - Data Engineering Technologies (online)
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Do you have any questions or need consultation?

 

Call us or write us – we are happy to help you with your inquiry.

Sibei Lin

Recruitment Counselor Online Program

Email: onlineprogram@constructor.university

Phone: +49 160 9780 2420