Data Science Graduate Certificate

According to the McKinsey Global Institute, the US will need to increase the number of graduates with data science skills by 60% to meet demand that is estimated to reach almost 500,000 jobs in 5 years. Data science includes IT expertise, but it also includes the ability to work with extremely large data sets and to communicate analytical findings to other professionals who can leverage those findings for strategic decision making.

The data science graduate certificate (15 credit hours) is a collaborative program among business analytics, computer science and information systems and prepares students to apply both data management and analytic techniques (including statistical and data mining approaches) to extract meaningful insights. Students acquire hands-on experience with relevant software tools, languages, data models, and environments for data integration, analysis and visualization. Working in teams, students communicate results of analysis effectively (visually and verbally) to a broad audience.

Graduate credits earned may apply to other MS and MBA programs subject to approval of the program directors.

Learning outcomes for data science Certificate students include:

  • Knowledge of how to integrate data from multiple sources and manage integrated data under a proper data management architecture.
  • Knowledge of how to apply analytics techniques and algorithms (including statistical and data mining approaches) to large data sets to extract meaningful insights.
  • Acquisition of hands-on experience with relevant software tools, languages, data models and environments for data integration, analysis and visualization.
  • Ability to communicate results of analysis effectively (visually and verbally) to a broad audience.

Curriculum (15 credit hours)

MS Business Analytics

BANA 6037: Data Visualization, two credits
BANA 6043: Statistical Computing, two credits
CS 6052: Intelligent Data Analysis, three credits
BANA 7042: Statistical Modeling, two credits
BANA 7046: Data Mining I, two credits
IS 7034: Data Warehousing for Business Intelligence, two credits
IS 8034: Big Data Integration, two credits

MS Information Systems/certificate only

BANA 6037: Data Visualization, two credits
BANA 6043: Statistical Computing, two credits
CS 6052: Intelligent Data Analysis, three credits
BANA 7038: Data Analytics Methods, two credits
IS 7034: Data Warehousing for Business Intelligence, two credits
IS 7036: Data Mining for Business Intelligence, two credits
IS 8034: Big Data Integration, two credits

Admission requirements

Applicants must have a baccalaureate degree and the appropriate coursework described below.

Admission to the data science certificate program is open in all three semesters. We recommend that students apply either in the fall or spring semester because many certificate courses are not offered in the summer semester.

Applicants to the program must provide transcripts and official university course descriptions to show that they have obtained a grade of at least 3.0/4.0 (B or better) for at least undergraduate level background courses in the following areas:

  • Database design and management: including experience with SQL queries and design and development of relational databases;
  • Statistics: including basic knowledge of probability distributions, hypothesis testing, and linear regression; and
  • Programming: including knowledge of data structures and experience developing medium-large software in C++ and/or java.

To learn more about this certificate please contact:

Headshot of Roger Chiang, PhD

Roger Chiang, PhD link

Professor, Department of Operations, Business Analytics, and Information Systems

313 Carl H. Lindner Hall

513-556-7086

Headshot of Kevin Mussman

Kevin Mussman link

Assistant Director of Graduate Recruitment

513-556-6904