COURSE CURRICULUM

The MSc in Data Intensive Astrophysics equips students with advanced skills in both astrophysics and data science, preparing them for careers in research, technical development, and data-driven scientific roles. The program combines core scientific principles with practical and computational techniques, ensuring students gain expertise in managing, analysing, and interpreting large and complex datasets. Core modules include research-focused projects, applied and theoretical machine learning, data science, and advanced techniques in physics and astrophysics, along with study and research skill development. These modules provide a strong foundation for understanding and applying computational methods to complex astrophysical problems, fostering critical thinking and problem-solving skills relevant to modern scientific research. Optional modules allow students to tailor their learning to specific interests, covering topics such as cosmology, exoplanets, galaxy formation, general relativity, gravitational waves, high-energy astrophysics, laser physics, and interstellar matter. A key component is a substantial research project, giving hands-on experience in applying data-intensive methods to real astrophysical problems, either within the School of Physics and Astronomy or through external collaborations. This practical experience, combined with theoretical knowledge, ensures graduates are highly skilled and ready to contribute to data-intensive research in astrophysics, scientific innovation, and other sectors where big data and computational expertise are in high demand.