Master of Science in Data Analytics for Science

Acquire immediately relevant training in modern data analytics, computational modeling, data visualization tools and machine learning techniques necessary to advance scientific discovery in your field.

The MS-DAS program is a one-year degree program, offering a unique foundation in modern programming, computational modeling, parallel computing and statistical analysis. Learn to apply these tools directly to scientific challenges and prepare for roles in commercial research, government and academia.

Coursework covers data analysis for science topics such as linear algebra, statistical modeling, scientific machine learning, computational modeling, high-performance computing and professional communication.

While Python is the primary programming language of instruction in the MS-DAS program, you will be introduced to other programming languages, such as SQL for data querying and R for statistical analysis and visualization.

View the MS-DAS curriculum.

MS-DAS students benefit from access to the Pittsburgh Supercomputing Center and have opportunities to work with these powerful technologies and domain experts to graduate with truly unique, advanced experience. PSC provides access to several of the most powerful systems for high-performance computing, communications and data storage available to scientists and engineers nationwide for unclassified research.

Learn more about PSC.

The semester-long capstone course allows you to work directly with industry partners on real-world, data-driven challenges. Drawing from a range of sectors, these partnerships connect you with professionals tackling complex scientific problems.

You and your fellow students will work in teams, guided by expert faculty, to apply advanced data analytics techniques to develop meaningful solutions. Regular check-ins with partners provide feedback on your approach while strengthening your communication and presentation skills. The capstone is a valuable opportunity to grow your network and connect with potential employers in science and data-focused fields.

Learn about the capstone experience.

MCS is here to support you throughout the admission process. We are eager to answer your questions transparently and connect with you on a personal level. Our FAQs provide basic information about the program — and we are happy to supply more detailed information via email.

Find answers to common data analytics master’s questions.

MS-DAS students have opportunities to interact with corporate partners through the capstone project and various networking events throughout the academic year. Carnegie Mellon’s Career and Professional Development Center is also available to discuss your career plans and assist with all aspects of your job search process.

The physical and life sciences industries need graduates with both a science foundation and knowledge of machine learning and AI. These tools are necessary for scientific innovation. The MS-DAS program uniquely positions students for success in fields such as therapeutics, pharmaceuticals, medical device technology, financial services and autonomous transportation, to name a few.