The Master of Science in Data Science provides the theoretical knowledge and practical skills required for dealing with the contemporary collection, exploration, analysis, and modeling of data along with the related challenges pertaining to inference and prediction. Emphasis is put on the mathematical foundations underpinning state-of-the-art methodologies: 

• Probability Theory

• Statistical modeling

• Numerical methods

• Optimization

• Markov decision processes for statistical learning

The core courses cover generally applicable theory and methods in a self-sufficient framework, while elective courses can tailor particular paths towards industry and business applications, or towards an academic career. The choice of electives can lead to a concentration, which is optional. 

Concentrations

• Fundamentals of Data Science

• Data Acquisition and Management

• Data Security

• Business Applications

• Analyze data with state-of-the-art modeling techniques with both high interpretability and prediction power.

• Make informed decisions based on the data.

• Effectively communicate analysis findings to non-experts.

• Work effectively in teams.

Program Educational Outcomes common to all concentrations:

• Explain the principles of the collection, storage, exploration, and analysis of data.

• Recognize the complexity of data and the assumptions underlying modeling strategies in real-life applications.

• Examine and implement efficient computational techniques for analyzing large-scale (big) data.

• Analyze and implement appropriate methods of inference, prediction and decision-making based on the data and complex structures.

• Develop and analyze data-based models.

• Effectively communicate analysis findings to an audience with a diverse background.

Program Outcomes specific to the concentration in Fundamentals of Data Science:

• Construct new relevant models and design algorithms tailored for challenging real-life situations.

• Interpret model outputs, infer, and make relevant decisions pertaining to applications.

Program Outcomes specific to the concentration in Data Acquisition and Management:

• Manage the collection, storage and exploration of data of large sizes and of various nature.

• Design and implement efficient distributed systems tailored for challenging real-life applications.

Program Outcomes specific to the concentration in Data Security:

• Manage the collection and storage of data of large sizes and of various nature, with an emphasis on privacy issues.

• Assess the vulnerabilities of a network, detect threats, and enforce appropriate security measures.

Program Outcomes specific to the concentration in Business Applications:

• Design, deploy and grow business intelligence systems tailored for challenging real-life applications.

• Interpret model outputs, infer, and make relevant decisions pertaining to business and industry-related questions.