Data Science Graduate Certificate

As an alternate to a full data science master’s degree program, a student can choose to pursue a data science certificate. This is a helpful alternative when a student needs to complete a graduate program quickly and for less cost. It is important to note that a certificate often does not hold the same weight in the job market as a full master’s degree.

Graduate certificates can be a good alternative if a candidate already has a master’s degree, but would like to increase their focus in a particular specialization or area. In some cases, credits from a graduate certificate can be applied towards a master’s degree in the future.

Enterprise Resource Planning Certificate

This online Certificate in Enterprise Resource Planning (ERP) is a gateway to additional professional and educational opportunities, such as SAP Boot Camp. Throughout the curriculum, students will:

  • Gain proficiency in the configuration, utilization and strategic application of ERP software
  • Learn the ins and outs of the ERP software by SAP
  • Employ their knowledge of ERP systems in any software environment
  • Enhance managerial and technical skill sets

Health Informatics Certificate

Prepare for a career in this growing field with a certificate program that you can complete in less than 12 months. Gain foundational knowledge in applying IT solutions to the healthcare context in just four courses and start your health informatics career sooner.

Explore and gain an extensive understanding of health informatics resources and tools, including:

  • Computer science
  • Communication
  • Information systems
  • Leadership

Certificate in Data Science in Computational Biology & Bioinformatics Certificate

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This 18-hour certificate was created for those who desire a greater understanding of how to work with big data at the intersection between life sciences and computational methods. Students in this data science certificate will learn to:

  • Evaluate solutions for data storage
  • Create software for analyzing large data sets
  • Implement data management solutions
  • Identify trends within data sets
  • Decide how best to use data in computational biology and bioinformatics
  • Compare cloud-based solutions for storing large data sets