The School of Business Informatics and Mathematics together with the School of Social Sciences start to offer the new degree program Mannheim Master in Data Science in Spring 2017. The degree program equips students with solid theoretical foundations as well as the necessary practical skills to obtain operational insights from large and complex data sets.
The acquisition and utilization of large quantities of data nowadays influences all areas of our daily life. The analysis and interpretation of large and often complex datasets - called Data Science - is a key factor for the economic success of businesses, the improvement of processes in public administration, as well as the advancement of science. The central obstacle that hinders companies, governments, and research institutions from realizing a larger number of Big Data projects is the lack of well-trained specialists who have the ability to integrate, analyze and interpret large amounts of data. With its new degree program “Mannheim Master in Data Science“ (MMDS), the University of Mannheim contributes as one of the first universities in Germany to closing this education gap.
Due to the traditionally strong quantitative and empirical orientation of Mannheim’s social sciences as well as due to the focus of Mannheim’s business informatics and mathematics on analyzing large data sets, the University of Mannheim provides the ideal environment for educating data scientists. The new degree program teaches students both the fundamental knowledge about methods of empirical social research and explorative data mining, and the skills to apply this knowledge on large data sets in practice. The program is highly interdisciplinary and is run as a collaboration of University of Mannheim’s Data and Web Science Group, Institute of Business Informatics, Department of Sociology, Department of Political Science, and Institute of Mathematics.
The MMDS degree program starts in the spring term of 2017 with 25 students per year. The program is financially supported by the second stage of the “Master 2016” extension program of the state of Baden-Württemberg. The target audience of the degree program are graduates of technically oriented Bachelor programs such as business informatics, business mathematics, informatics, mathematics and statistics, as well as graduates of quantitatively oriented Bachelor programs in social and economic sciences such as business administration, political sciences, sociology, and economics.
Structure and Content
The program is structured into the five blocks Fundamentals, Data Management, Data Analytics, Projects and Seminars, and the Master’s Thesis.
Fundamentals: The goal of the fundamentals block is to align the previous knowledge of students from different degree programs. Graduates from computer science and mathematics acquire the required knowledge in empirical research (in particular, data collection and multivariate statistics). Graduates from the social sciences and other fields acquire the required knowledge in computer science (in particular, programming and database technology).
Data Management: One of the central challenges in the Big Data area is to handle the enormous amount, speed, heterogeneity, and quality of the data collected in industry, the public sector, and science. The Data Management block covers methods and concepts for obtaining, storing, integrating, managing, querying, and processing large amounts of data. The block includes courses on modern data management technology (such as parallel database systems, Spark, and NoSQL databases), data integration, information retrieval and search, software engineering, and algorithms.
Data Analytics: The Data Analytics block forms the core of the study program. It provides courses ranging from data mining, machine learning, and decision support, over text analytics and natural language processing, to advanced social science methods such as cross-sectional and longitudinal data analysis. The range of methodological courses is enhanced by courses on optimization, visualization, mathematics and information, and algebraic statistics.
Projects and Seminars: The Projects and Seminars block introduces students to independent research and teaches the skills necessary to successfully participate in and contribute to larger data science projects. The block consists of research seminars, individual projects, team projects, as well as data science competitions. The projects are conducted jointly with industrial partners and/or support ongoing research efforts of participating institutes.
Master Thesis: In the master thesis, students apply what they learned throughout the program. The master thesis has a duration of 6 months. Students are encouraged to write their thesis either in the context of research projects conducted by participating institutes or together with an industrial partner.
More information about the degree program and how to apply for the program is found at http://www.wim.uni-mannheim.de/de/fakultaet/studiengaenge/msc-in-data-science/.