The M.S. in Data Science covers basic and advanced methods in statistical inference, machine learning, data visualization, data mining, and big data, all of which are essential skills for a high-performing data scientist. To be admitted to the program, we require a basic background in Mathematics (calculus, linear algebra), Statistics (probability and basic stats) and Software Development (programming, data structures and algorithms). Courses consist of formal lectures as well as hands-on programming projects. The program curriculum uses the Python programming language with its data science libraries and features tools like R for statistical analysis and Tableau for data visualization.
Students work on homework assignments and projects covering both theory and applications on real data with guidance from the professor and teaching assistants.

