In studying Data Science, students learn how to work with quantitative and qualitative data, ask interesting questions, evaluate claims, draw inferences, and effectively communicate datadriven answers to real-world problems. Data scientists are professionals who turn data into information, so mathematical and statistical knowledge is important. But Data Science is not just math and statistics; data scientists also need skills in the following areas:

• Writing computer code to analyze large data sets. Good programmers have self-reliance, but also know when to ask for help. They enjoy working in a logical and detail-oriented way and are persistent in the face of difficulties.
• Being curious and creative problem solvers. Curiosity is characterized by a desire to ask questions, seek the answers, and acquire an underlying knowledge of why things happen in a particular way.
• Being effective collaborators. Data scientists have to be able to work independently at times, but there are also many situations where they need to collaborate with colleagues.
• Facing down challenges. When things go awry, the data scientist needs to assess how to make a "course correction" to get the project back on track for successful completion.
• Communicating results in writing, in visuals, and in spoken form. After working diligently to arrive at interesting conclusions, it's important to communicate those conclusions clearly and effectively.

Interested students are advised to begin their program of study in their first year by taking Calculus I (MAT 121) and Introduction to Data Science (DSCI 110). They should also make an expeditious start on the computer science requirements.

Students are advised to consult with a member of the Data Science faculty to plan a four-year course of study as early as possible, as several of the required courses are only offered every second year.