The 2-year master program Data Science for Society and Business (DSSB) is a highly selective program for students of business and social sciences aiming to become data science experts. The program is also of high interest to students with backgrounds in health and environmental sciences aiming to expand into big data analytics, data-driven and computational social science, based on their strong quantitative background.
During two exciting years, graduates gain cutting edge competences, tools and methods to discuss, model, predict and solve the pressing challenges of digital societies, modern organizations and competitive businesses.
The truly multidisciplinary program combines a broad course offering from multiple social and data science disciplines with 3 elective tracks to allow for individual diversity and further specialization. With a focus on high employability, DSSB graduates are best prepared for quickly growing, global professional and academic career options resulting from digitization.
Students who are interested in business accumulate extensive digital knowledge for their international business careers. With the expertise in business analytics, business management and predictive modeling they build the in-demand technical, analytical and communications skills essential to enhance their management knowledge and apply it to solve complex business challenges.
Aiming to become tomorrow's entrepreneurs, intrapreneurs and data managers graduates manage large data sets and drive organizational change and optimization by understanding the target groups, their needs and predict behaviors and trends to optimize businesses and create sustainable ideas for the future.
Our master program enables students with interests in economics, media, political and other social sciences to analyze and understand unstructured heterogeneous data about humans and their interactions with the help of Artificial Intelligence, Machine Learning, and Statistics.
By applying data science expertise students can observe in real-time how social life enfolds, how networks grow, or how social dynamics and innovation emerge. These insights can be used to better decode and predict the logic of social behavior, opinion formation and economic trends.
For students who want to focus on health or environmental problems our master program offers a wide range of tools and methods to collect, evaluate and understand digital health and planetary data.
With the aim of making the world a better place, this knowledge can be used to illustrate the occurrence of certain diseases, predict their chances of cure, detect environmental threats, and monitor the success of countermeasures.
“Data science is so exciting because it creates new communities and liberates us from disciplinary boundaries."
"Our DSSB master program invites students to our international campus to approach the dynamic field of digital data and digitalization from social, business, engineering and natural science perspectives.
The leitmotif of the program is our commitment to cutting-edge research, problem orientation, and innovative projects.
DSSB is a door opener for promising careers in all industry sectors as well as in PR, journalism, political think tanks, government, international and non-governmental organizations.“
5 reasons why you should study Data Science for Society and Business (DSSB) at Constructor University
- Unique interdisciplinary modular program with elective tracks for individual diversity and specialization that promotes personalized career goals
- A cutting-edge demanding academic program with access to innovative research, a close relation between teachers and students, shared learning experience and innovative learning environments
- Maximum focus on employability and preparation for the demands of global career paths in all areas of data-driven professional and academic fields
- A graduation rate of 90% reflects the university’s high academic standards and the intense support level with in small classes with favorable student-to-teacher ratios
- Benefit from Constructor University’s direct access to the leading digital and tech companies, consulting firms, NGOs and top research institutes as well as a large global Alumni network
The master program Data Science for Society and Business study program teaches international students with strong backgrounds in social sciences (e.g. business, economics, demography, media studies, political science, psychology, sociology,) how to make use of rapidly growing digital data resources and new computational tools and methods to potentially solve the challenging interdisciplinary problems in their professional or academic field.
The program may also be interesting for students with a background in humanities, natural or technical science who want to focus on innovative social data analytics and pressing social and business questions emerging from digitization.
Students of the DSSB program thereby benefit from a broad course offering in various social, data and business sciences and the close cooperation with computer sciences, environmental and life sciences.
In addition, the program also promotes individual diversity and specialization. DSSB students can pick and choose course offerings from the 3 elective tracks based on their individual interests and career plans
- The Society and Business Track covers computational social science approaches, smart city, and transport concepts as well as principles of consulting, sustainable economics, and supply chain finance.
- The Health & Environmental Track connects socially relevant data science questions with insights and techniques from the natural sciences (health, medical, environmental sciences)
- The Data Science Track allows students with a strong mathematical or computing background to dive deep into data mining, data analytics and machine learning
At the end of the 2-year program DSSB graduates will have expertise in digital contents and data science skills to responsibly and capably solve core problems in future organizations and digital societies.
- They can identify, analyze, interpret and critically access the social causes and consequences of digital transformation of societies in all of its legal and ethical implications and aspects
- They are able to apply cutting-edge analytical and quantitative skills to correctly model and interpret scientific results, to make valid predictions and to derive thoughtful conclusions and interventions for pressing social and business problems
- Students have learned to manage big data, develop statistical models and convincingly present them to a science and non-science audience by applying plausible writing, communication and presentation techniques and visualization tools
- They will be able to program well in at least one computer language and know about state-of-the-art computational and software tools
The Curriculum at a glance
The MSc Data Science for Society and Business program is composed of foundational lectures, specialized modules, interactive seminars, tutorials and applied project work. These lead to a master thesis that can be conducted in close collaboration with research, institutional or industry partners on or even off-campus i.e. at a partner university, a political organization or at a company site. The program takes four semesters (two years). The following table provides an overview of the modular structure of the program. The program is partitioned into five areas (Core, Elective, Methods, Discovery, and Career) and the Master Thesis. All credit points (CP) are ECTS (European Credit Transfer System) credit points. In order to graduate, students need to obtain a total of 120 CPs.
Schematic study scheme
Core modules describe and analyze the machine-social context, the changes and the challenges new information technologies impose on today’s and future firms, entire economies and societies. They also teach students data science approaches, new models and analytical techniques. Hence, we aim at three units consisting of two 5 CP modules for research on digitization and societies (10 CP), digital transformation in business (10 CP), and data science and artificial intelligence concepts (10 CP).
Methods courses are key in data science. Programming skills, innovative, dynamic models and experimental methods as well as most up-to-date software lay the groundwork for understanding, replicating and contributing to research.
Discovery modules immerse students into diverse applications. Faculty from different disciplines introduce to up-to-date data science applications. Invited experts from business, public administration and other organizations reveal their digital data needs and solutions. These diverse experiences and insights lead to innovative experimentation in a data science lab and culminate in an individual capstone project in which students bring their theoretical and practical expertise together to creatively answer pressing social and data science problems, i.e. in health education, social media marketing, robotics, data security or digital government. Students who prefer to complete an internship with a company, or public organization can exchange the capstone project, and two of the mandatory elective career modules for this off-campus learning experience.
Modules in the career area aim at broadening the intellectual skills of students and boost their employability. Language modules and seminars on ethical and legal questions help to understand people with other cultural backgrounds and to understand normative concerns about the digitalization of our societies. Targeted modules on communication and career skills directly support students to exchange and function well in professional environments. Students who prefer to complete an internship with a company, or public organization can exchange the capstone project, and two of the mandatory elective career modules for this off-campus learning experience.
Electives allow students to expand and connect their expertise with other subjects. Courses in business, computer science, criminology, spatial sciences, public health and supply chain management also allow specialization.
The Data Science for Society and Business graduate program attracts students with diverse career goals, backgrounds and prior work experience.
Students can choose to strengthen their knowledge by focusing in one of 3 different areas:
- Society and Business
- Data Science
- Environmental & Health
These are recommended focus tracks. Students may however choose combination of the non-mandatory courses.
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The MSc Data Science for Society and Business (DSSB) graduate program is a highly selective program for students who have completed their BA / BSc in the social sciences (e.g. business, economics, political science, psychology, sociology,) who want to become a data scientist with an interest in business and social science research questions.
We are also open to accept students from the humanities and natural science (e.g. history, health or other neuro sciences with a quantitative orientation).
DSSB is a truly interdisciplinary program that combines a broad course offering from diverse social and non-social science disciplines with elective tracks for individual diversity and specialization.
By combining on- and off-line learning tools in core and method courses, students with diverse cultural and knowledge backgrounds and individual needs are quickly integrated. Remedial online learning allows to close mathematical or technical knowledge gaps.
Students thereby benefit from a close relation between teachers and students, small classes, shared learning experience and innovative learning environments.
To further gain professional and research practice, students have access to the data science lab, may engage in capstone projects, choose an elective internship or participate in public big data challenges.
This study program is part of the School of Business, Social & Decision Sciences.
The School of Business, Social and Decision Sciences focuses on interdisciplinary research and education in business sciences, finance and economics, political sciences, as well as in fields related social interactions and to cognitive processes underlying behavior of individuals, groups, or institutions.
Key disciplines in the school include Management Science, Finance, Economics, Industrial Engineering, Logistics, Political Science, Cognitive Psychology, and Sociology.