The program objectives are well described by the following intended learning outcomes. On successful completion of the program, graduates will be able to:
- Handle large amount of data using computational tools;
- Extract significant features from the data using scientific programming and statistical learning;
- Select appropriate hardware for different computational tasks;
- Interpret time-dependent data using concepts of stochastic processes;
- Utilize quantitative skills to make predictions;
- Provide solutions to optimization problems and for decision making through data-based modeling; and
- Adopt an innovation-minded attitude in exploring new uses of data-driven modeling.