Post-Baccalaureate Certificate in Applied Data Science

Certificate Level: Graduate
Admission Requirements: Bachelor's degree
Certificate Type: Post-Baccalaureate
Number of Credits to Completion: 15.0
Instructional Delivery: Online; Face-to-Face
Calendar Type: Quarter
Expected Time to Completion: 1 year
Financial Aid Eligibility: Not aid eligible
Classification of Instructional Program (CIP) Code: 11.0104
Standard Occupational Classification (SOC) Code: 15-1132

About the Program

The aim is to provide a strong foundation in this emerging area, with a focus on the application of data science methods for solving problems or gaining insights. The certificate program may also serve as an onramp to a Master of Science in Data Science, if completed with predetermined grade requirements.

Admission Requirements

Post-Baccalaureate Certificate in Applied Data Science accepts applicants who hold Bachelor degrees from an accredited university, and offers them an opportunity to learn a variety of foundational and applied data science topics. Please visit the College of Computing & Informatics' website to learn more about admission requirements.

Additional Information

For more information about this program, visit the College of Computing & Informatics' website, and/or contact:

  • Yuan An, PhD, Associate Professor, Department of Information Science, College of Computing & Informatics
  • Jane Greenberg, PhD, Alice B. Kroeger Professor; Director, Metadata Research Center; Associate Department Head for Graduate Affairs, Department of Information Science, College of Computing & Informatics
  • Christopher C. Yang, PhD, Associate Professor, Department of Information Science, College of Computing & Informatics
  • Jake Williams, PhD, Assistant Professor, Department of Information Science, College of Computing & Informatics

Program Requirements

Required Core Courses
DSCI 511Data Acquisition and Pre-Processing3.0
DSCI 521Data Analysis and Interpretation3.0
Elective Courses9.0
Choose 3 courses from the following:
Organization of Data and Information
Data and Digital Stewardship
Social Network Analytics
Information Retrieval Systems
Information Visualization
Data Mining
Introduction to Data Analytics
Total Credits15.0

Sample Plan of Study

Term 1Credits
DSCI 511Data Acquisition and Pre-Processing3.0
DSCI 521Data Analysis and Interpretation3.0
 Term Credits6.0
Term 2
Electives6.0
 Term Credits6.0
Term 3
Elective3.0
 Term Credits3.0
Total Credit: 15.0
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