M.S. in Data Analytics

M.S. in Data Analytics

M.S. in Data Analytics

The Master of Science in Data Analytics at Rowan University is designed for individuals with a Bachelor's degree in a STEM related field who are looking to expand their knowledge and opportunities in Data Science. The program has a strong background in Data Mining, Modeling, Statistical and Machine learning, but also includes potential concentrations in Health Data Analytics or Business Data Analytics for students with those interests. If no concentration is chosen there are a variety of electives so that students can increase their knowledge of Computer Science, Statistics, or Visual Analytics. The program is based on industry needs, as well as guidelines of the Commission on Accreditation for Health Informatics and information Management Education (CAHIIM) and of the Technology Accreditation Commission of the Accreditation Board for Engineering and Technology (ABET). Students will be prepared to use algorithms, statistics, and technology to make informed decisions from massive amounts of data, to manage streamed data or data stored in massive data warehouses, and to visually analyze and present information. Courses are designed to provide expertise in the data sciences and train students to solve problems with complex sets of structured and unstructured data commonly found in any industry.

 

Curriculum

The M.S. in Data Analytics program consists of 10 courses and a total of 30 graduate semester hours (s.h.). Students may enroll in this program part-time or full-time.

Foundation Courses
Applicants must have successfully completed the following courses (or their equivalents) at an accredited institution: Calculus II, Probability and Statistical Inference for Computing Systems, Linear Algebra, Introduction to Object-Oriented Programming or Computer Science and Programming, and Data Structures and Algorithms or Data Structures for Engineers.

Coursework

The following courses make up the M.S. in Data Analytics program.

  • 10 Courses/ 30 Semester Hours
  • Foundation Courses: Yes
  • Graduation / Exit / Thesis Requirements: No
Required Courses
Course Number
Title
S.H. (Credits)
DA 02510 Visual Analytics 3
DA 02515 Data Warehousing 3
DA 02505 Data Mining I 3
STAT 02515 Applied Multivariate Data Analysis 3
Health Data Analytics Concentration
Course Number
Title
S.H. (Credits)
DA 03510 Patient Data Understanding 3
DA 03505 Data Quality and Web/Text Mining 3
DA 01505 Data Analytics Capstone Practicum 3
DA 03520 Healthcare Management 3
  Choose 2 Courses from Elective Bank 6
Business Data Analytics Concentration
Course Number
Title
S.H. (Credits)
STAT 02525 Design and Analysis of Experiments 3
MGT 07500 Managerial Decision Making Tools 3
MGT 97600 Predictive Analysis 3
DA 01505 Data Analytics Capstone Practicum 3
  Choose 2 Courses from Elective Bank 6
No Concentration
Course Number
Title
S.H. (Credits)
DA 01505 Data Analytics Capstone Practicum 3
  Choose 5 courses from Elective Bank 15
Elective Courses
Course Number
Title
S.H. (Credits)
DA 03515 Patient Data Privacy & Ethics 3
DA 03520 Healthcare Management 3
STAT 02525 Design and Analysis of Experiments 3
CS 07570 Information Visualization 3
DA 02605 Data Mining II 3
DA 03505 Data Quality and Web/Text Mining 3
DA 03510 Patient Data Understanding 3
CS 04530 Advanced Database Systems: Theory And Programming 3
CS 07540 Advanced Design And Analysis Of Algorithms 3
CS 07556 Machine Learning 3
ECE 09555 Advanced Topics In Pattern Recognition 3
MGT 07500 Managerial Decision Making Tools 3
MGT 97600 Predictive Analysis 3
STAT 02514 Decision Analysis 3
STAT 02530 Applied Survival Analysis 3
 
Total Program Semester Hours: 30
 

Admissions Requirements

The following is a list of items required to begin the application process for 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.

  • $65 (U.S.) non-refundable application fee

  • Bachelor's degree (or its equivalent) from an accredited institution of higher learning

  • Official transcripts from all colleges attended (regardless of number of credits earned)

  • Current professional resume

  • Typewritten statement of professional objectives

    • Provide reasons for pursuing the program. Describe how you might use this program to advance your career (educational goals beyond the master's level, if applicable, are also relevant).
  • Two letters of recommendation

    • While the official Recommendation Form is required, an actual letter from the recommender is preferred.
  • Minimum undergraduate cumulative GPA of 2.5 (on a 4.0 scale)

  • Submission of official GRE test results is highly recommended

 

Start Dates & Application Deadlines

The chart below details available entry terms for the M.S. in Data Analytics 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.