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Graduate Certificate in Data Analytics

The Graduate Certificate in Data Analytics at Thomas Edison State University was developed in partnership with the Institute for Statistics Education at Statistics.com.

Data analytics is a rapidly expanding, interdisciplinary field that incorporates computer science, statistics and mathematical modeling with applications in business, government, life sciences and social sciences. The certificate program responds to the need for professionals to have an understanding of the ways that data analytics can be harnessed to interpret massive datasets, inform strategic planning and optimize business performance. The certificate is also a valuable credential for IT professionals looking for more immersion in the data analytics field and those helping organizations investigate complex issues and identify and resolve challenges.

The certificate is a natural credential extension for graduates of the University’s Bachelor of Science degree in Data Science and Analytics. Those who can benefit from the program typically have undergraduate degrees in business, operations research, management science, analytics, mathematics, engineering, computer science or in lateral technical or quantitative fields. Credits earned in the certificate program can be applied to the Master of Science in Data Science and Analytics program.

Credit Distribution Chart:

Course Number Degree Requirements Credits
DSI-620 Risk Simulation and Queuing 3
DSI-601
- or -
DSI-604
Predictive Analytics 1 – Machine Learning Tools: Python
- or -
Predictive Analytics 1 – Machine Learning Tools: R
3
DSI-610 Optimization – Linear Programming 3
DSI-621 Integer and Nonlinear Programming and Network Flow 3
Total   12

Data Analytics Certificate Outcomes

Upon completion of the certificate, students will be able to:

  • Demonstrate knowledge of statistical data analysis techniques utilized in decision making.
  • Apply quantitative modeling and data analysis techniques to the solution of real world challenges.
  • Communicate findings of data analysis and effectively present results using data visualization techniques.
  • Use data mining software to discern patterns and trends, establish relationships and identify a course of action that will inform strategic decision making and optimize business performance.