Your Curriculum Structure
M.Sc. Data Analytics and Decision Science (DDS) offers a comprehensive program of core courses in machine learning, mathematical and heuristic optimization and data-driven decision making. These courses are accompanied by a wide range of elective courses offering deep-dives into specific application areas. Our courses combine demanding and cutting-edge research with practical projects and challenges. We continuously review and expand the set of electives to cover the latest trends and stay abreast of technological change.
The two-year full-time program consists of seven key building blocks, some of which can be customized to meet your individual needs and interests. You may also enrol in a German language course at no extra cost.
DDS Essentials (10 CP to be completed in semester 1): The “DDS Essentials” consist of two courses that cover and refresh relevant essentials in mathematics, statistics, algorithms and data structures. These modules lay the foundation to participate successfully in the core courses in Data Analytics and Decision Science, as well as in some of the application areas and specializations.
Data Analytics (10 CP to be completed in semester 1 and 2): The block “Data Analytics” consists of three modules. The module “Predictive Modeling” covers the fundamentals in data handling and data quality issues, predictive modeling and validation of business- and use- cases, as well as evaluation of predictions. The course “Machine Learning” will focus on the fundamentals and cutting edge developments in machine and deep learning.
Decision Science (15 CP to be completed in semester 1 and 2): This block consists of three modules: The module “Optimization Models” introduces the concepts behind building state-of-the art decision models that are able to capture the combinatorial explosion of options, including networks and linear and integer programs. The module “Design and Analysis of Algorithms” focuses on modern methods to solve these optimization models. The course covers algorithms not only for deterministic problems but also techniques from robust optimization and algorithmic game theory, which allow to handle uncertainty in the decision making process. The module “Heuristic Optimization” covers the fundamentals of metaheuristics and the challenges encountered when designing high-performance heuristics for complex planning tasks in different domains.
Analytics Project (10 CP to be completed in semester 2): The Analytics project is a practical exercise that complements the lectures from the Decision Science and Data Analytics blocks. Teams of 3–6 students work together on a practically motivated analytics project and go through almost the entire analytics process using machine learning and optimization techniques: formalization of the problem, modeling, understanding, gathering, and cleaning of the data, algorithm selection and development, implementation, computational solution, visualization and interpretation, and documentation of results. The students learn how present their results to both a practice-oriented and a scientific audience.
Management and Soft Skills Electives (10 CP to be completed in semester 2): Students choose two of the following elective courses to deepen their managerial competences:
- Engineering, Culture and Society by using Design Thinking Methods
- Digital Work
- Strategic Technology Management
- Managing the Innovation Process
- B2B Marketing
- Service and Technology Marketing
- Start-Up and Growth Management
- Entrepreneurial Marketing and Finance
Technology Electives (5 CP to completed in semester 2): Students choose one of the three elective courses:
- Advanced Machine Learning
- Principles of Data Mining
- Industrial Logistics
Internship or Study Abroad (15 CP to be completed in semester 3): Students apply their skills in an industry work placement at global enterprises such as Deutsche Post DHL, PTV Group and others, or deepen their knowledge by studying at an international university,
Application Areas (15 CP to be completed in semester 3): Students gain detailed insights in the following domains:
- Digital Operations and Supply Chain Management
- Optimization of Logistics Systems
- Economic Modeling of Energy and Climate Systems
Master Thesis (30 CP to be completed in semester 4): By writing a master thesis at the end of the program students demonstrate their ability to solve a methodological or analytic challenge using the knowledge acquired during the program and the methods of scientific research.
Extracurricular Offer: German Language Course
Learning another language is an important part of a successful career. Becoming proficient in German is also an essential precondition for succeeding on the German job market, both for an internship during your studies or a permanent position thereafter. As an extra offer within the DDS program, we give you the option to complete an intensive German language course (either in semester 1 or 2) to broaden your cultural understanding and enhance your career options. The costs for the course are covered by your tuition fees.