Artificial Intelligence and Data Analytics (MSc)

Program overview

This English-taught Master's programme prepares you to build data-driven organisations where vast, complex datasets are transformed into actionable knowledge. You will learn how to apply artificial intelligence and advanced analytics to support evidence-based corporate decision-making across different business functions.

The curriculum focuses on turning “big data” into insights that managers can use to improve strategy and operations. Coursework and projects emphasize practical approaches for extracting value from data and integrating analytic results into business processes.

Graduates are equipped to work in areas such as marketing, logistics, corporate controlling and customer relationship management, helping companies make smarter, data-informed decisions and design more effective services and processes.

Key facts and focus areas

• Degree: Master of Science (MSc)
• Language of instruction: English
• Field: Business Administration
• Location: Neu-Ulm, Germany
• Core aim: Convert large, complex datasets into knowledge for fact-based corporate decision-making
• Typical application areas: marketing, logistics, controlling, customer relationship management (CRM)

Curriculum overview

This MSc follows a structured three-semester path, beginning with a campus-based first semester in Neu-Ulm that establishes core foundations in information systems, management, and AI. The second semester can be spent abroad and focuses on advanced technical topics and the organisational value of IT. The third semester—also optionally abroad—is devoted to research and the master’s thesis, supported by academic-writing and information-systems research preparation.

The program blends modules that address enterprise application and process management, consulting and interpersonal skills, and technical subjects such as Big Data, AI, NLP and deep learning. Students finish by producing and defending an independent research or applied thesis in the field of information systems and data analytics.

Key modules

• Enterprise Application Engineering
• Consulting
• Interpersonal Skills
• Strategy and Performance Management
• Digital Process Management
• Big Data and AI
• Business Value Creation with IT
• Business Application Re‑Engineering
• Advanced Natural Language Processing (NLP)
• Deep Learning
• Data Platform Architectures
• Elective (student choice)
• Academic Writing
• Information Systems Research
• Master’s Thesis and Thesis Colloquium

Intended learning outcomes

• Understand and evaluate enterprise application engineering and how IT supports business strategy and performance.
• Apply concepts of digital process management and business application re‑engineering to improve organisational workflows.
• Use Big Data, AI, advanced NLP and deep‑learning methods to extract insights from large and unstructured data sources.
• Design or assess data platform architectures suitable for scalable analytics workloads.
• Translate technical solutions into business value and communicate recommendations effectively to stakeholders.
• Conduct independent information‑systems research, produce an academic Master’s thesis, and present and defend results in a colloquium setting.

Graduates are prepared for roles that require both technical expertise in AI/data engineering and an understanding of business value creation. Typical career paths include data scientist, machine learning engineer, AI consultant, data platform architect, analytics manager or roles in business units (marketing, logistics, controlling, CRM) that leverage advanced analytics.

Because the programme combines technical modules with strategy and consulting skills, alumni can work in industry, consulting firms or continue into research-oriented roles, supported by the Master's thesis and academic writing/research training.