COURSE CURRICULUM

The MSc in Data Science for Renewable Energy is an intensive one-year full-time program aimed at students and professionals seeking to apply data science to the renewable energy sector. The course blends foundational training in Python programming and data mining with specialized knowledge in renewable energy technologies such as solar, wind, and marine energy. Students gain practical experience in analyzing renewable energy data and explore how advanced data science techniques can improve the performance and integration of these systems. The curriculum includes core modules in programming, data mining, and professional development, ensuring students are equipped with both technical expertise and the broader skills needed for successful project management and communication. The solar energy engineering module covers resource estimation, system design, and integration, while the fluids engineering module focuses on energy extraction from wind, waves, and currents, alongside the technical, policy, and environmental considerations of renewable projects. A central component of the program is the dissertation, where students undertake an independent research project that applies data science methods to a real-world renewable energy challenge. Projects may be industry-linked and allow students to investigate topics like machine learning for energy prediction or statistical analysis of performance data. This hands-on work builds on classroom knowledge and helps students deepen their expertise in both data science and energy systems. Students also have the option to expand their learning in areas such as artificial intelligence, power systems, or data visualisation, making the course adaptable to diverse career paths. Whether continuing into research or entering the renewable energy industry, graduates leave with the analytical, technical, and practical skills needed to make a meaningful contribution to the field of sustainable energy.