Courses & Semesters

Introduces major clean-technology pathways (e.g., renewables and environmental technologies) and how they translate into viable projects and ventures. Emphasizes innovation strategy, market and policy context, and project development/management.

Covers practical AI/ML approaches for clean-technology challenges such as energy efficiency improvement, fault diagnosis, predictive maintenance, and environmental monitoring. Students develop applied models and communicate results through project-based outputs and reporting/presentation.

Builds competence in energy economics, sustainability reasoning, and economic evaluation of clean-technology choices. Use cases and applied activities (including life cycle thinking and optimization perspectives) to support decision-making in low-emission technology adoption.

Provides statistical and econometric foundations for evidence-based analysis and decision support. Focuses on regression modelling, inference, time-series concepts, and the use of software tools to analyze real datasets and communicate results clearly.

Introduces optimization and operational research methods for engineering and technology problems. Emphasizes modelling, linear programming and key algorithms (including network/graph problems), supported by software-based evaluation and applied assignments/projects.

Develops intercultural competence for global technology and industry environments. Covers culture and communication frameworks, leadership/negotiation/mediation, inclusivity and ethics, and the role of English as a global lingua franca, with case-based and discussion-driven assessment.

Prepares students for rigorous research and applied studies in clean technologies. Covers quantitative/qualitative/mixed methods, data acquisition, case-study logic, desk/field approaches, and research strategy—directly supporting dissertation readiness through method-focused tasks.

A synthesis-oriented module where students transform real-life technological issues into structured projects. Emphasizes literature work, data acquisition and screening of alternatives, solution design/model development, and presentation/defense of a substantial paper-style deliverable.

Focuses on hydrogen-based systems, ammonia and other power-to-X options, storage technologies, and system integration issues. Uses socio-economic/environmental framing and case studies, typically assessed through a substantial applied project plus reporting/presentation elements.

Hands-on training in data mining, predictive analytics, and optimization using RapidMiner for business and clean-tech decision-making. Students build end-to-end workflows (preprocessing → modelling → evaluation → interpretation) and present actionable insights.

Covers waste management and waste-to-energy/valorization pathways within circular-economy logic. Uses real case studies (e.g., biorefinery options, biogas, decentralized processing) and evaluates environmental/economic implications through coursework and examination.

An individual capstone project written in English, demonstrating the ability to apply the Program’s theoretical and methodological tools to a professionally relevant clean-technologies management topic. Scope is agreed with the supervisor and culminates in a written dissertation (typically with an oral defense under Program procedures).