Data Science Courses

Data Science aims at understanding statistical data characteristics and generation of data-driven descriptive and predictive models for practical applications in specific domains. Data science workflows involve a variety of steps including data collection, exploration, cleaning, feature extraction, model estimation, evaluation and visualization. Creation of data science workflows requires theoretical and practical knowledge in statistics, programming, machine learning and big data management.

Computer Science (Bachelor)

BA-INF 035 - Datenzentrierte Informatik

Datenmanagement und Analyse für große Datenbestände; insbesondere praktische und theoretische Grundlagen relationaler Datenbanken sowie praktische und theoretische Grundlagen des maschinellen Lernens.

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 as well as 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. 

Computer Science (Master of Science)

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. The module topics include data structures, data representation and analysis methods, and algorithms that enable analysing spatio-temporal data and building predictive models effectively and effectively. Furthermore, we will study the corresponding evaluation techniques and novel 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. 

MA-INF 4324 - Seminar Advanced Topics in Data Science 

This module concentrates on specialized topics in data science, with a particular focus on spatio-temporal data analytics and its applications in specific domains (e.g., mobility, smart cities). 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.