Data Science, Advanced Graduate Certificate

Prior to applying to this program, students must have completed MSDS 420-DL Database Systems and Data Preparation and MSDS 422-DL Practical Machine Learning or are expected to possess equivalent knowledge and skills.


To earn a certificate, students must complete any four of the MSDS electives:

Course Title
MSDS 410-DLSupervised Learning Methods
MSDS 411-DLUnsupervised Learning Methods
MSDS 413-DLTimes Series Analysis and Forecasting
MSDS 431-DLData Engineering with Go
MSDS 432-DLFoundations for Data Engineering
MSDS 434-DLAnalytics Application Engineering
MSDS 436-DLAnalytics Systems Engineering
MSDS 440-DLReal-Time Interactive Processing and Analytics
MSDS 442-DLReal-Time Stream Processing and Analytics
MSDS 450-DLMarketing Analytics
MSDS 451-DLFinancial Machine Learning
MSDS 452-DLWeb and Network Data Science
MSDS 453-DLNatural Language Processing
MSDS 454-DLApplied Probability and Simulation Modeling
MSDS 455-DLData Visualization
MSDS 456-DLSports Performance Analytics
MSDS 457-DLSports Management Analytics
MSDS 458-DLArtificial Intelligence and Deep Learning
MSDS 459-DLKnowledge Engineering
MSDS 460-DLDecision Analytics
MSDS 462-DLComputer Vision
MSDS 464-DLIntelligent Systems and Robotics
MSDS 470-DLTechnology Entrepreneurship
MSDS 472-DLManagement Consulting
MSDS 474-DLAccounting and Finance for Technology Managers
MSDS 475-DLProject Management
MSDS 476-DLBusiness Process Analytics
MSDS 480-DLBusiness Leadership and Communications
MSDS 485-DLData Governance, Ethics, and Law

In some cases, students who have completed equivalent coursework previously may be allowed to replace the required course with another course in the field.

Please note that courses completed in the certificate program cannot be transferred to the corresponding graduate degree.