Data Science[go to overview]
Winter Term 2022 / 2023
Data Science is an emerging field that seeks to discover and explore new ways of exploiting data for a range of domains and problems. With individuals and organisations producing vast amounts of real-time heterogeneous data, there is greater demand than ever to manage and analyse data effectively.
This module aims to introduce students to the concepts and theories that underpin Data Science, provide an understanding of how they are used and the potential impacts of data use on organisations and society more generally. It is structured around three areas:
- an introduction to Data Science and Big Data
- topics related to the Data Science process, e.g. data pre-processing, representation, analysis and presentation
- issues surrounding the application of Data Science in practice, e.g. consideration of wider societal issues.
Students will be taught both theoretical and practical aspects of data science through a mixture of formal lectures, self-directed learning tasks, and practical sessions.
Students are expected to work in groups to complete weekly assignments. In order to complete the module (6 ECTS), students first have to achieve a score of at least 60% in these weekly exercises, which then qualifies them to sit the final exam. The threshold to pass the exam is 50%.
The module is available to students enrolled in various programmes offered by Fachbereich 4. For further details on eligibility and on how to enrol, we refer to KLIPS. OLAT will be used for sharing learning materials and for further module-related communication.