Master in Applied Mathematics for Network and Data Sciences

At Mittweida University of Applied Sciences, applications are due 15 May for the following winter semester.

Applied Mathematics for Network and Data Sciences at Mittweida University of Applied Sciences addresses the mathematical foundations of artificial intelligence, machine learning, data science, cryptography, and network analysis. The programme takes an algorithmic view of mathematics as a technology-driven field, combining mathematical rigour with relevance to current applications in areas such as Industry 4.0, forensics, medical technology, digital communication, and e-commerce. Over 4 semesters, students complete obligatory courses in Computational Intelligence and Machine Learning I and II, Foundations of Modern Cryptography, Cryptanalysis, Advanced Graph Theory and Network Algorithms, Simulation and Visualisation, Topics in Modern Analysis, and Communication Skills. Elective modules span Computational Statistics, Discrete Mathematics, Functional Models for Machine Learning, Digital Video Analysis, and others. The third semester is dedicated to a five-month research internship in industry or at a university, supported by a Research Seminar; the thesis topic typically develops from this placement. The fourth semester consists of a five-month Master's thesis concluded with a colloquium. Students engage with faculty research across machine learning, discrete mathematics, cryptography, and stochastic processes in biomathematics, and are free to select their own thesis topic. The programme suits graduates with a mathematics background who want to direct their work toward computational intelligence, network science, and data-driven applications in academic or professional settings. All courses are in English at Mittweida University of Applied Sciences in Mittweida.