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Data Analytics Graduate Certificate

The impact of your certificate

“Big data” is rapidly becoming a driving force for competition across multiple industry sectors. Thanks to the rise of smart, Internet-connected devices—and enterprises seeking to capture the attention of people holding those devices—the amount of data being produced globally will reach 44 zettabytes by 20201.

The ability to analyze, decipher, and translate such large amounts of data is critical—and it’s creating a huge demand in the workforce. By 2020, data science/analytics job openings are projected to grow 15%2.

The Data Analytics Graduate Certificate enables you to:

  • Learn core foundational knowledge in data science and data analytics.
  • Gain an interdisciplinary grounding in big data that prepares you for a field that is predicted to grow significantly.
  • Develop the knowledge and skills to pursue a career in data analytics.
  • Provides a path to continue your education and pursue a Masters of Science in the following programs:
  • Examine how data is collected, stored, and retrieved; how data can be extracted from large, structured/unstructured datasets; how to analyze information using data mining and machine learning; and how to use information design and visual analytics to analyze and present results.

Data Analytics Graduate Certificate Curriculum


The Data Analytics Graduate Certificate curriculum provides the foundational knowledge to bridge to professional master’s degrees utilizing “big data” and the skills to make data-driven decisions in any discipline. The program consists of four required core courses (16CR) developed by an interdisciplinary committee of active data researchers.

Learning Outcomes

Students who complete the core courses will be able to:

  • Use standard tools for data acquisition/management and basic statistical tests and models to perform quantitative data analysis on large and complex data sets.
  • Select, plan, and implement storage, search, and retrieval components of large-scale structured and unstructured information repositories.
  • Provide data scientists with properly structured, accurate, and reliable access to information needed for investigation.
  • Set up and run learning algorithms on various data sets, test models on new data, and evaluate results.
  • Use R to explore data, produce summary statistics, perform statistical analyses, use packages for data mining and machine learning, and use visualization tools to present and evaluate data.
  • Systematically use visualization techniques for supporting the discovery of new information as well as the effective presentation of known facts.
  • Choose appropriate visual languages for representing various kinds of data.
  • Communicate the results of data analysis to a non-expert audience.

Program Requirements

Core Requirements:

  • DA 5020 – Collecting, Storing, and Retrieving Data (4 credits)
  • DA 5030 – Introduction to Data Mining/Machine Learning (4 credits)
  • PPUA 5301 – Introduction to Computational Statistics (4 credits)
  • PPUA 5302 – Information Design and Visual Analytics (4 credits)

16 total semester hours required.

Data Analytics Graduate Certificate Curriculum

Overview Program Requirements


  1. IDC. The Digital Universe of Opportunities: Rich Data and the Increasing Value of the Internet of Things. April 2014.
  2. Louis Columbus. Forbes. IBM Predicts Demand For Data Scientists Will Soar 28% by 2020. May 13, 2017.



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