About
Big data, machine learning and cloud computing have fundamentally changed how we live and work. Data science is the application of these technologies to solve difficult problems in several domains. Probability and statistics provide the underlying mathematical foundation. The core knowledge and skills of data science are applicable to a broad range of application domains.
ECU Advantage
The ECU Master of Science in Data Science program is offered in both face-to-face and online formats. The program is designed to provide students with practical skills balanced with theoretical knowledge and professional practice. It prepares leaders and innovators who will help reduce costs and improve quality of care through innovative solutions to challenging problems in health care ? all driven by big data decision-making. Graduates will have the ability to think critically in making decisions based on data and deep analytics, communicate analysis results effectively to diverse audiences, participation multidisciplinary teams to accomplish a common goal, and gain knowledge of contemporary issues appropriate to the data science discipline.
What You Will Study
Applicants to this program are required to follow the admissions requirements and process as stated in the admission and retention section of the graduate catalog and the graduate admissions website. To be admitted to the program, applicants must have earned a bachelor's degree in computer science or a related field. A minimum cumulative undergraduate GPA of 3.0 and a minimum score of 30th percentile on the GRE General test are required for regular admission. Those who do not meet the requirement may be admitted by exception. Decisions will be made on a case by case basis. Nonnative speakers must submit an acceptable score on one of the language tests approved by the Graduate School or have evidence of at least 1 year of college/university study in the United States.
Students with bachelor's degrees in engineering, mathematics, statistics, physics, chemistry, or similar analytic and quantitative disciplines may be required to complete additional courses before being admitted to the degree, such as discrete mathematics, data structures, as recommended by the graduate program director.
A minimum cumulative GPA of 3.0 must be earned for all graduate courses. No more than 6 s.h. of course work evaluated as a C may be counted toward the degree.
The degree requires a minimum of 30 s.h. as follows:
- DASC 6000 - Data Science Methods I
- DASC 6005 - Data Science Methods II
- DASC 6010 - Big Data Analytics and Management
- DASC 6020 - Machine Learning
- DASC 7000 - Thesis
- DASC 6995 - Research Project
Choose one of the following options:
A thesis is required for this option. Students summarize their research in the form of a formal written document and deliver an oral presentation. Thesis research is typically conducted over two semesters. Six (6) s.h. count toward the degree requirements.
Twelve (12) s.h. of 6000-level data science (DASC), computer science (CSCI), software engineering (SENG), or other graduate courses approved by the graduate program director are required for this option. The semester hours from SENG courses must not exceed three (3) s.h. The semester hours from graduate courses outside of data science (DASC), computer science (CSCI), and software engineering (SENG) must not exceed nine (9) s.h.
To select electives, go to the list of CSCI, DASC, and SENG electives in part III.
A research project with a written report is required for this option. Students select topics for their projects in consultation with research advisors prior to the beginning of the last semester of study. The project involves collecting research literature on a topic of interest, critically examining it, and summarizing the research in the form of a formal technical report. This option may also involve developing software systems or proof of concept systems. Students must deliver an oral presentation of their findings. The research project is typically completed during the last semester of study. Fifteen (15) s. h. of 6000-level data science (DASC), computer science (CSCI), software engineering (SENG), or other graduate courses approved by the graduate program director are required for this option. The semester hours from graduate courses outside of data science (DASC), computer science (CSCI), and software engineering (SENG) must not exceed nine (9) s.h.
To select electives, go to the list of CSCI, DASC, and SENG electives in part III.
Eighteen (18) s.h. of 6000-level data science (DASC), computer science (CSCI), software engineering (SENG), or other graduate courses approved by the graduate program director are required for this option. The semester hours from graduate courses outside of data science (DASC), computer science (CSCI), and software engineering (SENG) must not exceed nine (9) s.h.
To select electives, go to the list of CSCI, DASC, and SENG electives in part III.
The coursework option requires an e-Portfolio comprehensive assessment. Please contact the program coordinator for more information.
Electives should be carefully selected after consultation with the graduate program director.
- CSCI 6030 - Information Extraction and Retrieval
- CSCI 6040 - Computational Analysis of Natural Languages
- CSCI 6045 - Cyber-Physical Systems
- CSCI 6050 - Digital Image Analysis and Understanding
- CSCI 6100 - Cryptography and Information Security
- CSCI 6120 - Computer Systems Architecture
- CSCI 6130 - Networking and Telecommunication
- CSCI 6140 - Mobile Communications and Wireless Security
- CSCI 6150 - Computer and Network Security
- CSCI 6220 - Topics in Language Design
- CSCI 6230 - Software Engineering Foundations
- CSCI 6300 - Cryptographic Protocols
- CSCI 6410 - Design and Analysis of Algorithms
- CSCI 6420 - Computability and Complexity
- CSCI 6510 - Distributed Computing
- CSCI 6600 - Database Management Systems
- CSCI 6710 - Developing e-Commerce Systems
- CSCI 6810 - Topics in Artificial Intelligence
- CSCI 6820 - Computer Graphics
- CSCI 6840 - Data Mining
- CSCI 6905 - Topics in Computer Science
- DASC 6015 - Data Visualization and Communication
- DASC 6030 - Information Extraction and Retrieval
- DASC 6040 - Computational Analysis of Natural Languages
- DASC 6050 - Digital Image Analysis and Understanding
- DASC 6060 - Health Informatics
- DASC 6070 - Decision Support in Health Care
- DASC 6090 - Data Science Practicum
- SENG 5000 - Programming and Data Structures Foundations
- SENG 5005 - Discrete Structures and Algorithmic Foundations
- SENG 6230 - Software Engineering Foundations
- SENG 6235 - Software Project Management
- SENG 6240 - Software Architecture and Design
- SENG 6245 - Software Construction
- SENG 6247 - Software Security Engineering
- SENG 6250 - Software Systems Modeling and Analysis
- SENG 6255 - Software Requirements Engineering
- SENG 6260 - Software Metrics and Quality Management
- SENG 6265 - Foundations of Software Testing
- SENG 6270 - Software Verification and Validation
- SENG 6275 - Dependable Systems and Software Reliability
- SENG 6280 - Process Management and Lifecycle Modeling
- SENG 6285 - Cloud Computing
All ECU graduate programs require students to successfully complete a comprehensive requirement. This program requires the following:
- Thesis option (thesis with oral presentation)
- Project option (research project with written report)
- Coursework option (e-Portfolio)
Students are required to complete a Plan of Study Form in consultation with the graduate program director before they begin their graduate study. This is usually done during the week before the first day of classes of first semester.