M.S. Data Science
Housed in the Department of Computer Science and offered in collaboration with the Department of Mathematical Sciences, the interdisciplinary Data Science program offers you the choice of a Computational or a Statistics track, while equipping you with the fundamentals and application tools to solve Data Science problems.
- Provide training in three core components of data science: machine learning, big data analysis and programming for Data Science.
- Provide training in applied statistics, particularly statistical inference.
- Cover applications and contemporary topics in Data Science.
- Apply statistical methods for decision making.
- Build and analyze predictive models from data using machine learning and statistical inference.
- Program Data Science applications in high-level languages such as Python and R.
- Analyze large datasets using high-performance computing and distributed computing methods.
- Compare the benefits and drawbacks of contemporary and advanced topics in Data Science.
- Make informed architectural decisions based on a good understanding of how available technologies differ and complement each other and what scalability and consistency trade-offs they provide.
Wu, Chase Qishi
Basu Roy, Senjuti
Professor and Associate Dean for Research
Borcea, Cristian M.
Chair & Professor