Carl H. Lindner College of BusinessCarl H. Lindner College of BusinessUniversity of Cincinnati

Carl H. Lindner College of Business

Data Science

The Data Science graduate certificate is a collaborative program offered between the Computer Science and Business Analytics programs.

Academic Director: Dr. Edward Winkofsky

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 be 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 graduate certificate in Data Science prepares students to apply analytic techniques and algorithms (including statistical and data mining approaches) to large data sets to extract meaningful insights. Students acquire hands-on experience with relevant software tools, languages, data models, and environments for data processing and visualization. Working in teams, students communicate results of analysis effectively (visually and verbally) to a broad audience.

This certificate is a collaborative program between Computer Science and Business Analytics. Graduate credits earned apply to MS, MEng, and MBA programs. Companies seeking data scientists include dunhumby, Procter & Gamble, Google, Twitter LinkedIn, Facebook, Amazon, Teradata, Microsoft, AT&T, Verizon, and many, many others.

 

Learning Outcomes for Data Science Certificate students include: 

  1.  Knowledge of how to apply analytic techniques and algorithms (including statistical and data mining approaches) to large data sets to extract meaningful insights. 
  2. Acquisition of hands-on experience with relevant software tools, languages, data models, and environments for data processing and visualization. 
  3. Ability to communicate results of analysis effectively (visually and verbally) to a broad audience. 

  

Curriculum (15 credit hours) 

Core Courses:

  • EECE 8075 (3 cr) Data Warehousing and Mining
  • CS 6052 (3 cr) Intelligent Data Analysis
  • CS 6065 (3 cr) Cloud Computing
  • BANA 6037 (2 cr) Data Visualization
  • BANA 7038 (2 cr) Data Analysis Methods
  • BANA 6043 (2 cr) Statistical Computing


Admission Requirements

  1.  Applicants must have a baccalaureate degree (BS or BA).
  2.  Applicants must have appropriate course work as described below.

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:

  1. database design and management: including experience with SQL queries and design and development of relational databases,
  2. statistics: including basic knowledge of probability distributions, hypothesis testing, and linear regression, and
  3. programming: including knowledge of data structures and experience developing medium-large software in C++ and/or java.

Course descriptions should be added in the online application.

To learn more about the Data Science Certificate please contact:

Julie Glassmeyer, Assistant Director, by email at Julie Glassmeyer or phone at 513-556-7031