Master of Science in Applied Information and Data Science

The MSc in Applied Information and Data Science equips students to become experts in designing, implementing, and communicating data- and AI-driven solutions for complex real-world challenges. Graduates are prepared for key roles such as data scientists, data engineers, analytics consultants, AI experts, or innovation managers in diverse sectors. The course fosters the ability to link technical know-how with domain understanding, ethical judgment, and communication skills to create impact with data.

The program targets career changers and professionals with backgrounds in business, engineering, social sciences, or IT who aim to acquire interdisciplinary, practice-oriented data science and AI competencies.
The master’s program helps students identify and use data’s potential when designing innovative products and services, new business models, and support functions for operations. It provides the students with solid technical, analytical, methodological, and applied skills as well as a strong sense of the economic and social possibilities of the data they use.

Graduates of the program can:

• Question and reflect on the data
• Collect, integrate, and pre-process data
• Process, explore, analyze, and interpret data
• Predict human and system behavior
• Visualize and tell stories about data
• Design and train AI applications
• Develop data- and AI-driven business models
• Design data products and services
• Apply data in a variety of settings
• Understand legal and ethical issues

Deep Tech is present across the curriculum, especially in modules on Big Data engineering, predictive and generative AI, applied machine learning, and deep learning. Students apply cutting-edge tools and techniques to address domain-specific challenges in sustainability, Internet of Things, logistics, geospatial systems, finance, healthcare, and more. Ethics, legal aspects, responsible AI, and data storytelling are embedded to foster critical reflection and communication of data insights.

The program spans 120 ECTS credits and includes required modules, electives, project-based learning, and a final master’s thesis. Learning formats combine on-site and online sessions, industry collaborations, coaching and project-based assignments. Teaching and assessment emphasize real data, peer learning, and formative feedback through lecturers and industry experts.