Why East Carolina University?
East Carolina University’s Master of Science in Data Science offers a unique focus on data science for the health care industry. Students must take required courses in health informatics and decision support in health care, and many health-related electives are also offered by this university located in Greenville, North Carolina. With the strong job market for health care careers and the increasing importance of data-driven decision-making in today’s hospitals and medical clinics, East Carolina University’s program is an attractive choice. Applicants are expected to enter the program having completed at least one undergraduate course in calculus, probability and statistics, and linear algebra.
Strong prior background in programming is also expected, with prerequisite coursework in algorithmic problem-solving using a higher-level programming language such as Java, Python, or C++ as well as a course on data structures and algorithms. ECU leaves the door open for students without a quantitative academic background and may accept relevant work experience instead of coursework. An undergraduate GPA of at least 3.0 is expected, and no standardized test results are required.
|University Name||East Carolina University|
|Name of Degree||Master of Science in Data Science|
|School or Department Administering Program||Computer Science|
|Cost per credit||$840|
|Tuition for Entire Program||$25,200|
|Test Requirements||None required|
|Prerequisite Courses and Skills||Waiver possible with work experience, or one course in each of: |
|Campus Visit Required?||N|
|Typical Time to Complete||Two years|
|When Can Students Start the Program?||Fall, Spring, Summer|
|Does the Program Include a Capstone?||No|
|Does the program include a practicum or internship?||Yes|
|Other Features that Make the Program Unique|
|Program Description||This 30-credit program, focusing on data science within healthcare, teaches students to clean, transform, integrate and aggregate data, determine the suitability of datasets, build descriptive, diagnostic, predictive, and prescriptive models, and use analytics and machine learning methods to generate actionable insight. Critical thinking, knowledge of contemporary issues, communication, and teamwork skills are also emphasized. The program can be completed within two years and includes a mandatory practicum.|
What will I Learn?
Students in the ECU MSDS learn about the processes of data science from data collection to actionable insight through a program that emphasizes communication, teamwork, and critical thinking about contemporary issues. The required coursework provides a robust general education in theory and techniques of data cleaning and collection, statistical model, analytics, and machine learning. Students then delve more deeply into domain knowledge with required courses on natural language processing, health informatics, and decision support within health care. The program provides a rigorous curriculum for aspiring data scientists who want to explore the use of big data within patient care, electronic health records, health policy, and other topics.
How much will the program cost?
Students finish their degree within two years and pay $840 per credit for a total of 30 credits, or just over $25,200 for the entire degree.
How does the program fit into my life?
The program is designed for the busy professional looking for flexibility while completing a rigorous academic program. Classes are 100% online, and no visits to campus are required. All classwork is completed asynchronously, meaning that the instructor provides course material such as lectures, discussion, and activities as a series of weekly modules, and students can choose when to complete that week’s content. Entry dates in Fall, Spring, and Summer mean that students can begin the program at the time most convenient for them.
The ECU program stands out for its clear and relevant learning objectives, its focus on data science for health care, and its range of exciting electives. Students who have less academic preparation in mathematics, statistics, or programming, or who want to pursue a domain specialization outside health care, may want to consider other programs.