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Graduate Certificate in Big Data

Earn your Graduate Certificate in Big Data

This certificate helps professionals understand massive datasets by having the analytics skills needed to work in this high demand field. Organizations need to manage Big Data as they continue to capture, store, search, share, visualize and analyze massive, unstructured, and complicated data sets. In response to the growing demand to manage Big Data across all sectors (private, public, government and academic), the Graduate Programs in Software department has created the Graduate Certificate in Big Data.

Students have the option to use the coursework from their graduate certificate to continue in a Master of Science degree program offered by Graduate Programs in Software.

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How to earn a graduate certificate

Graduate Certificate in Big Data Requirements

To complete the Graduate Certificate in Big Data, you must complete the following four courses (12 graduate semester credits) with at a GPA of 2.7 or better. Students will be expected to have a prior background in Python or take SEIS 603 Foundations of Python I:

Four Required Courses:

  • SEIS 630 Database Management Systems and Design
  • SEIS 631 Data Preparation and Analysis
  • SEIS 732 Data Stores and Feature Design
  • SEIS 745 Data Lake Engineering

View the Graduate Programs in Software course catalog.

Graduate Certificates that Work for You

Convenient Schedule

Classes are offered in-person and online weeknights from 5:30 – 8:30 p.m., Monday – Friday.

View Our Course Schedule

Course Delivery Mode

All programs in the Software Engineering and Data Science department at the University of St. Thomas are offered in CoFlex mode, i.e. the student has the flexibility to attend classes either in-person or online.

Inclusions and restrictions:

  • CoFlex course delivery mode is available to U.S. citizens, permanent residents, and students on work visas.
  • International students or students receiving certain scholarship benefits are ineligible to take the online option and must attend classes in-person.
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Get the Facts

Attend an Information Session

Attend an online information session to learn program details. Our programs serve working professionals with busy lives. Set your own pace and start fall, spring or summer. Classes are offered in-person and online weeknights from 5:30 – 8:30 p.m., Monday – Friday. We look forward to meeting you.

Register For A Session

FACULTY

All full-time tenured faculty hold Ph.D. degrees and offer extensive industry experience. Adjunct faculty are selected based on professional experience and educational credentials.

Dr. Abe Kazemzadeh headshot

Dr. Abe Kazemzadeh

Dr. Abe Kazemzadeh is an Assistant Professor in the University of St. Thomas Software Engineering and Data Science department. His undergraduate interest in linguistics led him to graduate studies in computer science that focused on natural language processing.

Dr, Abe Kazemzadeh
Syed Ali Naqvi head shot

Syed Ali Naqvi

Ali Naqvi has worked in many roles over the past 25+ years including Software Department Manager at Starkey Hearing Technologies, Lead Software Engineer, SCRUM Master, and Agile Transformation Coach at Thomson Reuters; Technical Architect and Senior Technical Analyst for Target Corporation; Software Architect at Object Technology Solutions Inc.; and Programmer/Tester at IBM Mankato, Minnesota.

Syed Ali Naqvi
Nathan Crawford head shot

Nathan Crawford

Mr. Nathan Crawford is an adjunct faculty member in the Software Engineering and Data Science department at the University of St. Thomas.  He is currently employed as a Principal Analytics Architect at Ecolab. Nathan enjoys teaching and working with students to improve their data management skills and to help students prepare for the next steps in their career.
Nathan Crawford

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