The use of data analytics tools, including artificial intelligence, machine learning and statistics, has become an increasingly vital part of conducting modern scientific research.

The M.S. in Data Analytics for Science (MS-DAS) program at Carnegie Mellon University is a degree program created for students seeking to acquire additional skills in many aspects of data science. Unlike existing degree programs designed with computer science or engineering backgrounds in mind, the MS-DAS program is tailored for students with backgrounds in the foundational sciences, such as biology, physics, math, chemistry or related fields.

Leveraging the world-class experts and technology of the Mellon College of Science and the Pittsburgh Supercomputing Center, students will be able to build on their science knowledge through learning modern programming languages for scientists, mathematical and computational modeling, computational methods such as parallel computing, high performance computing, machine learning techniques, information visualization, statistical tools and modern software packages.

MS-DAS graduates can expect to have competitive skills for careers in academia, commercial research, government and more. A key part of the program will be a semester-long capstone project in collaboration with industry partners.

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