Applied AI for Digital Production Management, MEng

Overview This programme trains you to extract value from the vast amounts of data generated in modern manufacturing. As industry digitalises, companies increasingly need specialists who can analyse production data and turn insights into strategic decisions that boost innovation, efficiency, competitiveness, quality and sustainability across the digital production chain. The course develops the analytical and decision-making skills demanded by contemporary production environments.

Curriculum and practice You will study topics such as machine learning, data analysis, data management and intelligent systems, together with modules like Advanced Statistical Methods & Optimisation that address the growing role of AI in production, logistics and technology management. Theory is reinforced through practical, industry-oriented learning: three case studies (in AI, intelligent systems in production, and production systems) are developed and supervised by engineers from manufacturing firms, giving you hands-on experience of real production challenges.

Learning environment and student support Teaching combines lectures, seminars and case-based work in small groups to ensure intensive tuition and personalised support. Studies are supported by modern science labs fitted with advanced equipment for high-tech AI work. Compulsory German lessons help you build the language skills useful for internships or employment in Germany, and Cham’s international, multicultural campus community offers a supportive environment for international students.

Program highlights (concise)

• Integrated modules covering machine learning, data analysis, data management and intelligent systems
• Advanced Statistical Methods & Optimisation to meet AI demands in production, logistics and technology management
• Three industry-supervised case studies in AI, intelligent systems in production, and production systems
• Balanced mix of lectures, seminars and practical case work
• Small study groups for personalised support
• State-of-the-art laboratories and technical infrastructure
• Compulsory German lessons to support career opportunities in Germany
• International, multicultural campus community with industry links

Program overview

This 18-month (three-semester) postgraduate programme is delivered entirely in English to reflect the global applicability of applied AI in production and logistics. Grounded in industrial engineering, the course combines core technical training in machine learning, data management and optimisation with practical, case-based projects that target real-world digital production challenges.

The curriculum balances foundational methods and tools with systems- and management-oriented topics. Early semesters concentrate on algorithmic and data skills applied to production and logistics, while later work moves toward integrating intelligent systems into digital production environments, technology and innovation management, and sustainability. The final semester is devoted to consolidation through a master's thesis and a two-part master's seminar (master's colloquium plus the "Career Start into German Technology Companies" seminar series).

Key modules (by semester)

• First semester:
  • Machine Learning and Deep Learning in Production and Logistics
  • Advanced Statistical Methods and Optimisation
  • Data Management
  • Production and Logistic Management
  • Digital Tools in Development and Production
  • Case Study: "AI Project"
• Second semester:
  • Technology and Innovation Management
  • Advanced Intelligent Systems
  • Case Study: "Intelligent Systems in Production"
  • Digital Production Systems
  • Case Study: "Production Systems"
  • Subject-Related Elective Course (FWP)
• Third semester:
  • Quality and Sustainability
  • Master's thesis
  • Master's seminar (two parts: Master's colloquium and Career Start into German Technology Companies seminar series)

Learning outcomes

• Apply machine learning and deep learning techniques specifically to production and logistics problems.
• Use advanced statistical methods and optimisation to analyse production data and improve operational decisions.
• Manage and structure production-related data for analytics and digital tools.
• Design and evaluate digital production systems and intelligent system components in industrial contexts.
• Understand technology and innovation management principles relevant to deploying AI in production environments.
• Tackle real-world challenges through case studies that bridge theory and practice.
• Demonstrate awareness of quality and sustainability issues in digital production.
• Complete an independent research or development project (master's thesis) and communicate results in academic and industry-focused settings, supported by a seminar series that includes preparation for careers in German technology companies.

Graduates will be prepared for roles that apply AI and data analytics in manufacturing and production contexts, such as AI/ML engineer for manufacturing, data scientist for production and logistics, production systems analyst, or technology and innovation manager. The programme’s strong practical focus and industry case studies aim to make graduates effective at implementing AI solutions to improve efficiency, quality, sustainability and competitiveness in production chains.

Demand is growing across manufacturing industries for specialists who can analyse big data, deploy intelligent systems, and support strategic decision‑making in Industry 4.0 environments. Alumni can expect opportunities in manufacturing companies, automation and robotics firms, logistics providers, and consulting organisations focused on digital transformation and smart production systems.