This Master of Science prepares you to turn large, messy data into clear, actionable insights. The curriculum covers scientific programming, data analytics, machine learning and data-driven decision-making, with a strong emphasis on practical, hands-on projects and the latest algorithms and tools. You’ll learn to tackle real-world problems and apply methods directly to business contexts.
The programme is especially relevant to logistics and supply chain management, where global operations, complex decisions and continuous data flows create rich opportunities for analytics. Built on KLU’s operations heritage, the teaching fosters an “operations mindset”: combining academic rigour with applied problem-solving, systematic and data-driven work, attention to operational detail, and a strategic, sustainability-aware leadership perspective.
Studying in Germany gives you access to a respected higher-education system and a strong labour market; graduates are legally allowed to stay in Germany for up to 18 months after finishing their degree to look for work. There is also a Corporate Sponsorship option—KLU partner companies may select and sponsor talented students, potentially covering up to full tuition and offering close collaboration through study projects, internships and master’s thesis supervision. For questions or to learn more, contact study@klu.org and consider joining an Open Day or other events to experience the programme first-hand.
Requirements & key facts
Duration & language:
Core focus and learning outcomes:
Practical experience & international exposure:
You should hold a recognised bachelor’s degree (or equivalent) and have a background suited to analytical work in business. Applicants with degrees in business or economics are preferred, but candidates from related quantitative fields can be considered if their bachelor’s programme included sufficient business coursework. The programme offers options to remedy missing business modules, so prior study gaps do not automatically rule you out.
There are different credit and mobility expectations depending on the study track. The standard track requires 180 ECTS from your bachelor’s degree; the fast track and the part‑time track require 210 ECTS. For the fast and part‑time tracks you must also demonstrate international experience during your bachelor’s studies—either one academic term abroad or an officially credited internship abroad.
Proof of English language ability is required; the programme provides several ways to demonstrate proficiency, so check the admissions page for acceptable tests and certificates. If you haven’t yet received your degree certificate, you may still apply by submitting your transcript of records.
Admission requirements (summary)
Winter Semester (International)
31 May 2026
Winter Semester (EU/EEA)
15 July 2026
Graduates will be prepared to apply advanced analytics and data science methods to business decision-making across sectors. Typical career pathways include roles in data analytics, data science, business analytics, and analytics-driven decision support—particularly within logistics, supply chain management and operations, where large-scale, real-time data and complex optimisation problems are common.
The programme’s practical projects, internship options and strong corporate links help build industry-relevant experience and networks. The up-to-18-month post-study work entitlement in Germany gives international graduates additional time to find suitable employment and transition into the German job market.
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