Data Science
In times of "Big Data", Data Scientists are experts in demand: Using methods from mathematics, computer science and statistics, they extract facts and knowledge from large amounts of data. The master's program "Data Science" is an interdisciplinary course of study jointly run by the Department of Computer Science and the Department of Mathematics and Natural Sciences at Darmstadt University of Applied Sciences.
Our Data Science - Study Programs
- Master's program Data Science, degree Master of Science (M.Sc.)
- Dual study model Master Data Sciene, degree Master of Science (M.Sc.)
Challenging topics
Data Scientists are in high demand as analysts, consultants or system architects in management and academia. They are needed in many industries, such as:
- Banks and insurance companies
- Trading companies
- Management and organizational consultancies, market research companies
- Social media, telecommunications, online retail and network management
- Logistics
- Healthcare, bio, pharmaceutical, chemical and medical industry
Synchronization modules for career changers
Even those who do not have a degree in mathematics or computer science can study Data Science. Synchronization modules are offered for lateral entrants, which are the basis for understanding the other modules (details in the module handbook).
- Methods of descriptive statistics, probability and inferential statistics.
- Object-oriented programming and design as well as algorithms and data structures
- Databases
- Operating systems and distributed systems
- Computer networks and IT security
Interesting and practical projects
Award-winning project by student Linda Rebstadt - Spark-based analysis of monitoring data of intensively monitored patients to identify anomalies: A use case of the Charité Health Data Platform
Virtual Desert Worlds - Digitizing millennia-old cult sites in Jordan to make them accessible to the general public as digital twins
Winning with nitrogen oxide - as part of a Machine Learning Challenge, nitrogen oxide pollution in Darmstadt was predicted on the basis of measured environmental data and with the help of artificial intelligence.
Exciting topics for master theses
- Anastasiia Quarz: Artificial intelligence guided positioning of active voxels in particle therapy treatment planning
- Samuel Kees: Data-Efficient and Iterative Metric Learning for Open Set Classification in an Industrial Setting
- Alisia Wendt: Arbitrage zwischen Kryptobörsen
- Lukas Klein: Machine learning applied to right censored survival data
List of all master theses incl. abstracts and posters
Strong industry partners
We have partnerships with many well-known companies for project and master's theses as well as for the dual study program variant. Further information is available under cooperation partners.
Christopher Wahl:
... I also find the studies very exciting, and I especially appreciate the great practical relevance. I've been able to apply most of what I've learned in the lectures directly to my work. So definitely thumbs up!
[Christopher Wahl completed a dual study program with the cooperation partner R+V]
Christophe Krech:
I have a topic that has to do with the application of artificial intelligence and machine learning in the real world.
[Christophe Krech on his master's thesis at Arvato Financial Solutions].
Ronny Horst:
At my university, Darmstadt University of Applied Sciences, you have a total of three practical phases in the dual Bachelor's program. The structure is generally the same, but each practical phase focuses on a different topic, such as working in a team or project management. ... When choosing the practical project, ORDIX AG takes the students' wishes into account, if possible. For example, I was able to choose a project in the field of Big Data.
[Ronny Horst about his practical phase at ORDIX].