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Fachbereich Informatik
FachbereichInformatik

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FB Informatik

M.Sc. DSAI - Structure

The course program divides into the following categories:

Mandatory modules: These modules cover knowledge specific to the Data Science and Artificial Intelligence program, and students have no choice regarding the required modules.

Required elective modules: These are related to Data Science and Artificial Intelligence core concepts and applications. Students have to choose modules from the category “Fundamentals of Data Science and Artificial Intelligence” for a total of 24 ECTS, and modules from the  category “Advanced Topics in Data Science and Artificial Intelligence” for a total of 18 ECTS.

Domain Knowledge:
These modules cover various application domains and transversal knowledge concepts, enabling the students to apply the core concepts learnt in the required and free modules to diverse scientific disciplines. Courses from at least two, at most four, application domains with at least 6 ECTS per domain must be selected, and students must gain in total 24 ECTS. Students can choose to study either in depth (select many courses from a few application domains) or in breadth (many application domains, with a typical 6 ECTS per module).
Please refer to the full table-style module handbook for module pre-requirements and more details.

DSAI Core Modules

The compulsory area DSAI (Mandatory Modules in DSAI) (54 ECTS) comprises two modules offered exclusively for this degree program: "Foundations of Data Analytics" and "Epistemology, Ethics and Privacy". In addition, a Master's project on DSAI and the final thesis are part of the compulsory module. The compulsory module "Foundations of Data Analytics" covers the mathematical and computational foundations for analyzing data. Examples include matrix calculation, multivariate stochastics, dimension reduction, classification, clustering and regression methods. The compulsory module "Epistemology, Ethics and Privacy" lays the foundations for the legally compliant and ethically acceptable use of data. In addition to the basics of data protection law, methods for "Privacy by Design" are covered and the requirements for value-oriented system design are discussed in general and using case studies.

Winter Semester

  • InfM-EEP Epistemology, Ethics and Privacy [EN] (6)
  • InfM-FDA Foundations of Data Analytics [EN] (6)
  • InfM-Proj/DSAI Project Data Science and Artificial Intelligence [EN] (9)

Winter / Summer Semester

  • InfM-Sem/DSAI Seminar Data Science and Artificial Intelligence [EN] (3)
  • Final Module (Thesis) [EN] (30)

DSAI Fundamentals

In the compulsory elective area DSAI (Fundamentals of DSAI) (24 ECTS), students acquire basic knowledge in the areas of data analysis and processing as well as the handling of large amounts of data. In addition, basic computer science knowledge is taught in the areas of theoretical computer science and software engineering.

Winter Semester

  • InfM-ALG Algorithms [EN] (9)
  • InfM-SSP Statistical Signal Processing [EN] (9)
  • InfM-SWA Software Architecture [EN] (6)

Summer Semester

  • InfM-DIS Databases and Information Systems [EN] (9)
  • InfM-ML Machine Learning [EN] (9)
  • InfM-NN Neural Networks [EN] (6)

DSAI Advanced Modules

In the specialization area DSAI (Advanced Topics in DSAI) (18 ECTS), the knowledge from the compulsory and compulsory elective areas is deepened in computer science-related subject areas.

Winter Semester

  • InfM-BAI Bio-inspired Artificial Intelligence [EN] (6)
  • InfM-BKIM Biostatistics and Artificial Intelligence in Medicine [DE] (6)
  • InfM-CV1 Computer Vision I [DE] (6)
  • InfM-IR Intelligent Robotics [EN] (6)
  • InfM-NLP Natural Language Processing and the Web [DE] (6)
  • InfM-OML Optimization for Machine Learning [EN] (6)
  • InfM-WV Knowledge Processing [EN] (6)

Summer Semester

  • InfM-CV2 Computer Vision II [EN] (6)
  • InfM-LT Language Technology [EN] (6)
  • InfM-RT Robot Technology [EN] (6)
  • InfM-SSV Speech Signal Processing [EN] (6)