Students in the M.S. in Data Science and Analytics program build a robust knowledge base and solid foundation in data science and analytics fundamentals, including big data and cloud computing, machine and deep learning, interactive and complex visualization methods, advanced databases, objects, algorithms, and complexity, text mining and natural language processing, and advanced mathematical and statistical modeling. Languages used include R, Python, and SQL. Students also engage in additional and critical skills including decision science, data communication, visual narrative development, teamwork, and complex problem solving techniques. Students who complete the program pursue careers in fields including business intelligence, analytics, and decision making, medical analytics, public policy, government, and political analytics, finance, marketing, and banking analytics, big data infrastructure and cloud computing, global health analytics, and many other data-dependent areas. The data science graduate program also serves as preparation for students who wish to enter a Ph.D. program in Data Science and Analytics, Applied Mathematics, Statistics, Computer Science, or Economics.