Bachelor of Science in Data Science

Analysts who use big data are employed by many kinds of institutions and in many different industries: government, businesses, financial institutions, healthcare, scientific research facilities, colleges and universities, and others.  The collection and use of big data continues to expand in all of these areas.  As businesses seek to maximize the value of vast stores of available data, employees will be needed to fill the growing demand for individuals who can learn from that data and predict and forecast consumer behavior.

The Bureau of Labor Statistics Occupational Outlook Handbook 2012-2013 reports that the employment of market research analysts is projected to grow more than 41 percent between 2010 and 2020. Even with that growth, predictions are that by 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills, as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions (Robert Walker, Ph.D., Computerworld, September 2013).

The Bachelor of Science in Data Science at Becker College is interdisciplinary and unique among undergraduate programs in the region. The program prepares students for success in an information-based global economy and prepares graduates to evaluate and analyze data science problems requiring the integration of computer science, mathematics, and other specialized disciplines (e.g., bioinformatics, business analytics, crime & policing analytics, cyberterrorism analytics, marketing & consumer analytics, financial & risk analytics, health analytics).

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For more information about the Bachelor of Science in Data Science, call 877.523.2537 or email admissions@becker.edu.

Upon successful completion of this degree, the student will:

  • Assess the challenges and opportunities presented by massive unstructured data across a variety of industries and organizations;
  • Practice inquiry and analysis through a systematic process of issue and method selection, data collection, data analysis, communicating findings, limitations and implications;
  • Implement  a variety of techniques and  technologies for analyzing massive datasets;
  • Explain key concepts, techniques, and current practices related to scalability, algorithms, architectures, and automation in big data;
  • Interpret, analyze, and validate the results of big data analysis;
  • Demonstrate written and oral communication skills in a variety of formats to technical and non-technical audiences;
  • Evaluate patterns in big data and make actionable insights and recommendations to decision-makers;
  • Execute a plan to strategically manage a data science project in an organizational setting;
  • Consider the ethical considerations of data science, including privacy and information security issues, and;
  • Experience project management through teamwork environments in laboratories, group projects, and internship experiences.

Data Science Specialization Requirement

Students graduating with a B.S. in Data Science must complete a specialization. Specializations are generally 12 credits but may require prerequisite coursework in order to enroll in courses within the specialization. The following specializations are proposed: Bioinformatics, Crime and Policing Analytics, Cyberterrorism Analytics, Business Analytics, Marketing and Consumer Analytics, Financial and Risk Analytics, and Health Analytics.

» Bioinformatics (12 Credits)
» Business Analytics (12 Credits)
» Crime and Policing Analytics (12 Credits)
» Cyberterrorism Analytics (12 Credits)
» Financial and Risk Analytics (12 Credits)
» Health Analytics (12 Credits)
» Marketing and Consumer Analytics (12 Credits)

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