Data-Intensive Computing
Big Data" refers to the rapidly growing amounts of data generated in science, technology and our daily lives. Technologies such as "cloud computing" and "multi-core processors" make it possible to process these large amounts of data. In order to gain meaningful knowledge from this flood of data, competencies in Data Science, scientific computing, parallel processing and algorithms are necessary. This study profile combines all these aspects and is equally interdisciplinary, theoretically sound and oriented towards current applications.
Graduates of the study profile "Data-Intensive Computing" are expected to acquire interdisciplinary competences in mathematics as well as selected natural and engineering sciences in addition to the fundamentals of computer science. Students are thus able to link interdisciplinary algorithms, methods and tools with real-world applications. As Data Analysts, Data Managers, Computational Engineers but also Computational/Data Scientists, students are thus optimally qualified for science and industry in their studies.
German name: Daten-intensives Rechnen
Designated Speaker / Deputy Speaker: Prof. Peter Sanders / Prof. Achim Streit
Special competencies acquired in the profile:
Graduates know basics in data analysis, simulations, data management, algorithms and security, and are able to further develop and optimize them.
They have developed a basic understanding in mathematics and selected natural and engineering sciences and can extract and specify the requirements from these disciplines for data-intensive computing.
You will be able to apply the portfolio of algorithms, methods and tools to develop interdisciplinary advanced and powerful solutions for natural sciences and engineering as well as an industrial application.
- The master thesis must be from the subject area of the study profile.
- At least 10 CP from each of the two compulsory elective subjects "Daten" and "Algorithmen und Parallelverarbeitung" must be taken.
- In addition, two of the advanced mandatory modules Rechnerstrukturen, IT Security (former: IT-Sicherheit; Sicherheit), Algorithms II (former: Algorithmen II), Advanced Artificial Intelligence (former: Fortgeschrittene Künstliche Intelligenz; Kognitive Systeme) (at least 12 CP) must be taken. If the advanced mandatory modules have already been examined in the Bachelor's degree, more LP must be taken from the other areas (compulsory elective subjects, elective block, complementary subjects).
- One of the following complementary subjects "Materialwissenschaften für datenintensives Rechnen“, „Mathematik für datenintensives Rechnen“ or „Betriebswirtschaftslehre für datenintensives Rechnen“ must be taken (9-18 CP).
- Additional thematically appropriate seminars, internships, or research practice may be taken in consultation with the profile coordinator.
- A total of at least 54 CP from 2.-5. and the elective block must be completed.
A bilingual list of eligible courses can be found on the German page.