Data Science Graduate Certificate
According to the August 2018 LinkedIn Workforce Report for the United States, the demand for data scientists is off the charts. Shortages of data science skills are present in almost every large US city. The national shortage for these skills exceeds 150,000 people, with particularly acute shortages in New York City, the San Francisco Bay Area, and Los Angeles. As more industries rely on big data to make decisions, data science has become increasingly important across all industries, not just tech and finance. Data scientists should have IT expertise and 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 (fifteen credit hours) is a collaborative program among business analytics, computer science, and information systems. This certificate program prepares students to apply both data management and analytic techniques (including statistical and data/text mining approaches) to extract meaningful insights from both structured and unstructured data. Students acquire hands-on experience with relevant analytics and data management tools, programming languages, data models, and IT architectures 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 MS and MBA programs subject to approval of MS/MBA program directors.
Learning outcomes
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/text mining approaches) to large data sets to extract meaningful insights.
- Acquisition of hands-on experience with relevant analytics and data management tools, programming languages, data models, and IT architectures for data integration, analysis and visualization.
- Ability to communicate results of analysis effectively (visually and verbally) to a broad audience.
There are two certificate tracks for Lindner College of Business graduate students. Certificate-only students will follow the MS-IS track.
Admission requirements
Admission to this program is very competitve and space is limited.
Applicants must have a baccalaureate degree (BS or BA) and the appropriate coursework 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. Course descriptions should be added in the online application.
- 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.
Admission to the data science Ccertificate program is open for all three semesters. However, we recommend students apply either in fall or spring semester because many certificate courses are not offered in summer semester.