Computational Data Analytics Certificate of Graduate Study (COGS) from Rowan University

Computational Data Analytics Certificate of Graduate Study (COGS) from Rowan University

The Certificate of Graduate Study (COGS) in Computational Data Analytics is intended for tech savvy industry managers who need to take advantage of big data opportunities.
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Overview

We have partnered with Rowan University to offer students who have successful completed the Analytics for Data Science (ADS) certificate an opportunity to stack that credential with one more course from Rowan University to earn their Computational Data Analtyics Certificate of Graduate Study (COGS).

Who This Degree Serves

Rowan Global Learning & Partnerships is Rowan University's vehicle to reach out and serve the needs of college students, working adults, lifelong learners, and the business community. 

Learning Outcomes

As a result of this program, students will be able to apply data analytics in any area of specialization. Students will be prepared to use algorithms, statistics, and technology to extract business intelligence from massive amounts of data, to manage streamed data or data stored in massive data warehouses and to visually analyze and present information.

Prerequisites

To apply to the program: 

There may be additional action or materials required for admission to the program. Upon receipt of the materials below a representative from the Rowan Global Admissions Processing Office will contact you with confirmation or indicating any missing items.

Required Courses

The Computational Data Analytics Certificate of Graduate Study is a part-time program offered in both a face-to-face format and remotely. It requires the completion of 12 semester hours. With an Analytics for Data Science (ADS) Certificate from Statistics.com, only one course (below) from Rowan University is required.

The only course required for this Computational Data Analytics Certificate of Graduate Study is the Visual Analytics course. This course is usually only offered in-person but is now offered remotely too. All other course requirements are waived with the completion of the Analytics for Data Science (ADS) certificate from Statistics.com

Required courses (2):

DA 02510 Visual Analytics
DA 02505 Data Mining I waived

 

For more information, please email the program director at Rowan University, Tony Breitzman (breitzman@rowan).

Elective Courses

Elective courses (2): All electives are waived with the completion of the Analytics for Data Science (ADS) Certificate from Statistics.com

DA 02515 Data Warehousing
Applied Multivariate Data Analysis
Data Mining II waived
Advanced Software Engineering
Information Visualization waived
Machine Learning waived
Advanced Topics In Pattern Recognition
Decision Analysis waived
Data Quality and Web/Text Mining

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Tuition and Fees

Only one (1) three-credit course is required to complete this COGS.  The tuition and fees for the course is $2,650.95

Rate Fees Per Semester Hour
$716 $167.65 $883.65

Note: This rate applies to the academic year 2019/2020 and is subject to change. Please contact Rowan University for more details.

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Frequently Asked Questions

Contact Rowan University Global Learning

Call (856) 256-4747

global@rowan.eduEmail
 
Locations

Enterprise Center
225 Rowan Boulevard
Glassboro, NJ 08028

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 Camden Campus
129 North Broadway
Camden, NJ 08102

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Start Dates & Application Deadlines

The chart below details available entry terms for the Computational Data Analytics Certificate of Graduate Study program as well as corresponding application deadlines. Submitting the Application Form is only the first step to beginning the admission process. All of the required materials listed above must be received on or before the application completion deadline for your desired entry term to be considered for admission to that term. We encourage you to complete the application form and begin submitting your materials at least one month before the deadline indicated.

Term Start date Application Deadline
Spring 2020 01/21/2020 11/01/2019
Summer 2020 05/19/2020 04/01/2020
Fall 2020 09/01/2020 07/01/2020

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