Data Science

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Program Mission

The mission of the program is to provide students with a rigorous, quality, integrated education in the fundamentals and advanced topics in computer science, software engineering, statistics, and mathematics, in addition to coursework in basic sciences, communications, social sciences and humanities. The program fosters the development of analytical, quantitative, computational, experimental, modeling and simulation skills in a collaborative environment. Our graduates will be prepared to meet the challenges presented by the explosive growth of big data sources, such as social media, consumer behavior, financial transactions, personalized healthcare, scientific instruments, etc. They will gain the knowledge as well as application skills necessary to address the opportunities and problems in a wide variety of industry and government jobs.

Educational Objectives

Within three to five years of graduating, alumni of the program are expected to achieve one or more of the following milestones:

1. Have successful careers in data science or careers in related areas of science and engineering or professional disciplines that benefit from an understanding of large data sets, such as technological fields, business, economics, medicine, law, finance, marketing, education, and sports.
2. Be valued contributors to private or public organizations as demonstrated by promotions, increased responsibilities, or other professional recognition.
3. Pursue advanced degree programs in data science and other disciplines.
4. Display commitment and leadership within the profession and community as demonstrated by contributions towards society.

Student Outcomes

By the time of graduation, the program enables all students to attain:

1. An ability to identify, formulate, and solve real-world problems using data science techniques
2. An ability to design and conduct experiments, as well as to analyze and interpret data using statistical, computational or mathematical methods
3. An ability to understand, manipulate, transform and supplement data as appropriate
4. An ability to effectively present results using data visualization tools
5. An ability to discuss problems and communicate findings in a non-technical language
6. An ability to function on multidisciplinary teams
7. An ability to communicate effectively both verbally and in writing
8. An ability to use current techniques, skills, and tools necessary for computing practices
9. An understanding of professional and ethical responsibility
10. A recognition of the need for, and an ability to engage in life-long learning

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