Data Science Major: ��ɫ��Ƶ, Greater Cincinnati Region

Program Type: Undergraduate

School: School of Computing & Analytics

The Bachelor of Science in Data Science is designed to prepare graduates to help organizations face the pressing question of how to use data effectively. Coursework that includes data analytics, mining and visualization, etc. will prepare students to address this exponentially growing technology and business industry need.

Foundational studies in mathematics, statistics, business and computer science will enable you to provide meaning out of vast amounts of data. This empowers you to solve problems for business, non-profit, government and research. You will learn how to clean data to enable processing of it, how to process data and present it. Your coursework provides you with depths in multiple fields that are needed for future advancements in all fields.

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Accreditation

The Bachelor of Science in Data Science program at ��ɫ��Ƶ (NKU) is accredited by the Computing Accreditation Commission of��. ABET is a nonprofit, non-governmental organization recognized by the Council for Higher Education Accreditation for global accreditation of post-secondary programs in applied and natural science, computing, engineering and engineering technology. At present, 4,361+ programs at 850+ colleges and universities in 41+ countries have received ABET accreditation.

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Program Contacts

Rasib Khan, Ph.D.
Associate Professor
Program Head, Computer Science & Applied Software Engineering
GH 504D
859-572-6025
khanr2@nku.edu

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Program Objectives, Student Outcomes, and Statistics

Students in the Spotlight

Emily Clemmons

Graduating Year: 2020

Education: Major in Data Science, Minor in Business Information Systems and Computer Science

Why Computer Science?

"Majors in the Computer Science Department are full of problem solving and challenges, something I knew I wanted in my major. Another drawing point is the wide array of industries that utilize Computer Science, which offers many paths to take post-graduation."

Experimental Learning

"I participated in an internship opportunity with Archer Daniels Midland’s Data and Analytics team where I worked to build a dashboard of Key Performance Indicators for the various teams in Data and Analytics. This gave me the chance to work on a team with people from different backgrounds, learn how to work with changing deliverables. I also was able to take part in Twitter Data Research with Dr. Marius Truta and Dr. Alina Campan."

Recommendations

"Get involved on campus in as many ways as possible. While course work is the extremely important, there are a lot of skills to be learned outside of the classroom as well. The soft skills I gained through on campus employment and leadership roles in organizations during my time in college have played key roles in allowing me to be successful in various professional opportunities."

After Graduation Plans

"I plan to work full-time, and then also pursue a Master's degree."

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Find Your Passions & Build Your Future

Students working on laptops in classroom

Flexible Course Offerings: Earn your degree��full-time��or��part-time. We offer classes at times that work with your varied schedule!��All classes are offered in daytime and evening hours. Many classes are also offered accelerated, hybrid format and/or online!
Outstanding Career Preparation: Build on your academic success by engaging in our different student organizations, on campus competitions,�� internship and co-op opportunities including virtual co-op programs. Co-ops and internships provide real-life work experiences in your discipline to hone your skills and provide a deeper understanding of your coursework.
Join the Game Changers:��NKU was the one of the first schools in the country and our region to offer an undergraduate degree in Data Science. It prepares you for jobs that are developing and being created while you are studying for your degree!
The courses in this program prepare you to be a Data Scientist, but you will also have a solid foundation for careers in the fields of Information Systems, Computer Science and Statistics.