About the Program

With the increasing availability of data, companies, governments, and other institutions are striving to convert information into actionable information and insight. In the past, students trained in singular disciplines such as computer science, operations research, or statistics had the skill set needed to analyze the required data. But the 'volume', 'velocity', and 'variety' of today's data and future data streams poses unique challenges and also creates unique opportunities. 

Present data sets requires more programming, mathematics/statistics, modeling skills, and domain knowledge than a traditional undergraduate curriculum offers. In fact, one of the obstacles that must be removed before government, business and social sectors are prepared to use large datasets to enhance their decision-making, is the acquisition of a trained workforce that can leverage it. It has been suggested that the US alone is facing a shortage of 140,000 to 190,000 workers with the analytical and managerial skills necessary to meet the rising challenge that increased data presents.

Decision makers require data and evidence before resources are committed. In the current environment, commitments are not made unless evidence supports that the opportunities are both cost effective and yield positive net benefits. Healthcare practitioners seek evidence-based medicine; social scientists engage in impact assessments; business analysts practice decision science and engineers and computer scientists desire facility with big data sets using a variety of statistical techniques. 

Our program requires technical courses from each college on our campus and is highly multidisciplinary. Taking a multidisciplinary approach, the curriculum is designed to leverage existing courses on campus and combine these with foundational courses in data science. This creates synergy among academic units on campus, provides flexibility in scheduling, and allows for timely completion of the program. Students with varied backgrounds can take different courses to suit their needs, based on interest and guided by faculty advisors. 

Curriculum Requirements

Students complete a minimum of 120 credits and receive a Bachelor of Science (B.S.) degree in Data Science. Requirements are available to download (PDF). 

Please note that beginning in Fall 2015, all freshmen must follow the Dearborn Discovery Core (DDC) requirements. 

Program Educational Objectives

Upon completion of the coursework, students in the data science core will have the ability to:

  1. Access, assess and manipulate data sets in order to extract meaningful information using statistical methods and mathematical models (Practical)
  2. Use the information gathered to build models capable of prediction and/or assessment (Practical)
  3. Communicate results and solutions in simple terms (Communications)
  4. Develop a clear understanding of ethical standards (Theoretical)