Courses

BA-INF 035 - Datenzentrierte Informatik
This module addresses data management and data analysis paradigms for large datasets. In particular, the module includes the practical and theoretical foundations of relational databases as well as the practical and theoretical foundations of machine learning.

BA-INF 150 - Introduction to Data Science (Einführung in die Data Science)
This module focuses on the data science process as a whole. This process involves obtaining, integrating and cleaning the data, exploratory data analysis, data modelling using statistical and machine learning methods, and model evaluation. The module pays specific attention to the application of relevant statistical methods to the data science workflows. Furthermore, analysis of selected data types is considered (e.g. time series, text data). Practical examples are demonstrated using the R programming language. 

MA-INF 4230 - Advanced Methods of Information Retrieval 
This module introduces the students to the advanced methods, data structures, and algorithms of information retrieval for structured and semi-structured data (including, for example, knowledge graphs, relational data, and tabular data). At the end of the module, the students will be capable of choosing appropriate data structures and retrieval algorithms for specific applications and correctly apply relevant statistical and machine learning-based information retrieval procedures.

MA-INF 4328 - Spatio-Temporal Data Analytics
This module introduces the students to the advanced methods, data structures, and data analytics algorithms for spatio-temporal data. At the end of the module, the students will be capable of choosing appropriate data representations, data structures and algorithms for specific applications and correctly applying relevant statistical and machine learning-based data analytics procedures.

MA-INF 4231 - Seminar Advanced Topics in Information Retrieval
This module concentrates on specialized topics in information retrieval. The students obtain skills in the independent, in-depth study of state-of-the-art scientific literature on specific topics, discussion with their peers and presentation to the scientific audience. We address statistical and machine learning-based information retrieval methods, including typical steps of the information retrieval process: data collection, feature extraction, indexing, retrieval, ranking, and evaluation. Specialized data representation and retrieval methods for selected data types and applications in specific domains.

MA-INF 4324 - Seminar Advanced Topics in Data Science
This module concentrates on specialized topics in data science. The students obtain skills in the independent, in-depth study of state-of-the-art scientific literature on specific topics,  discussion with their peers and presentation to the scientific audience.

MA-INF 4232 - Lab Information Retrieval in Practice
This module concentrates on the practical application of information retrieval methods to solve retrieval problems on real-world data and evaluate proposed solutions. Participants acquire basic knowledge and practical experience in designing and implementing information retrieval systems for specific data types and applications.

MA-INF 4325 - Lab Data Science in Practice

This module concentrates on practical experience in data analytics. Participants acquire basic knowledge and practical experience in the design and implementation of data science workflows for specific data types and applications.