Data Science

To efficiently manage, process, and compute with a wide array of data types. This will be achieved through both high- and low-level programming languages. The graduates should be able to interact with software engineers who build infrastructure around these tasks, as well as consumers and producers of the data. They should also be prepared to learn new technology, such as new programming languages or new software tools, as they becomes useful in their domain.

To master probabilistic and statistical thinking. When faced with a new task or a decision, they should be able to recognize the non-determinism of the outcome, and assess with some confidence the likelihood of various potential outcomes.

To take an abstract task involving a data set, and perform standard data analysis. These include, identifying the core structure and patterns of the data if it exists, building a function that automatically predicts the outcome for as of yet unseen data, and communicating concisely these findings to consumers of the data.

To interact meaningfully with experts in some technical data domain. These experts may be for instance engineers, scientists, marketers, or policy setters. In particular, our graduates should have some non-trivial experience interacting with the finer details of at least one data rich domain.