COURSE CURRICULUM

The Data Science and Artificial Intelligence for Sustainability MSc offers a comprehensive curriculum through compulsory and elective modules to address global sustainability challenges. Compulsory modules include GIS and Spatial Data Management, which focuses on managing geographical data using tools like ESRI software, covering spatial data models, mapping, and visualization for environmental decision-making. Decision Science equips students with systems thinking to evaluate environmental management strategies, considering trade-offs and uncertainties. Scientific Python develops coding skills for data analysis and visualization, utilizing Python libraries and geospatial data. Data Analytics for Sustainability introduces predictive and descriptive analytics, emphasizing ethical data practices for sustainability solutions. Artificial Intelligence for Energy Systems explores AI applications like neural networks to enhance energy system planning and operation. Sustainability and Environmental Assessment teaches lifecycle analysis and environmental impact assessment to evaluate renewable energy technologies. Students choose one elective from options like Computational Fluid Dynamics for Renewable Energy, which covers CFD techniques for modeling renewable energy systems, Energy Entrepreneurship, focusing on starting and managing ventures, or Energy Systems Case Studies, which integrates multidisciplinary knowledge for real-world project analysis. These modules collectively train students to leverage data science, AI, and digital tools to tackle complex sustainability issues, such as energy security and ecosystem management, ensuring alignment with goals like Net Zero emissions. Graduates gain skills to analyze data, develop innovative strategies, and address environmental, economic, and social trade-offs, preparing them to contribute to sustainable development.