Online MS in Health Data Analytics
Bouvé College of Health Sciences
Lead the future of healthcare with data-driven decision-making
100%
online
18+
Months
32
Credits
$24k
$750 per credit hour
About the program
The Master of Science in Health Data Analytics equips students with the technical expertise and industry knowledge to harness healthcare data for impactful, data-driven decision-making. Combining a strong analytics core with healthcare-specific coursework, the program prepares graduates to extract insights, identify trends, and navigate the complexities of the healthcare ecosystem—positioning them for success in analytical and leadership roles in the field.
Unique Features
- Strong Analytics Core – Gain expertise in data acquisition, mining, statistics, and visualization, along with hands-on experience using industry-standard tools like R, SAS, and Python.
- Healthcare-Specific Focus – Learn to navigate the complexities of healthcare data, including payer, provider, and regulatory needs, as well as the evolving business of healthcare.
- Flexible, Fully Online Format – Designed for working professionals, the asynchronous structure allows students to balance their studies with career and personal commitments.
- Career-Ready Skills – Graduates are prepared to extract insights, communicate findings to nontechnical stakeholders, and drive data-informed decisions that improve patient outcomes and healthcare systems.
Admission pathways for all backgrounds
Skip the application - let your performance pave the way. With the Online MS in Health Data Analytics' Fast App pathway, you can skip the traditional application process and use your performance on two initial courses to secure your place in the program.
Complete two “pathway” courses (part of the required Analytics Core), get a ‘B’ grade or better, show proof of your bachelor’s degree by the time you complete the two courses, and you’ll join the next cohort in the full degree program.
⇒ Submit your Fast App to join the program today.
You can also apply to the program using the standard graduate application for direct admission consideration.
Not ready for a full master's degree?
The Analytics Stack Track is a flexible, affordable way to earn your online analytics master’s degree at Northeastern—starting with a valuable credential at a reduced cost.
How it works:
Begin with the Online Graduate Certificate in Data Analytics Engineering, which covers the full analytics core required for three master’s programs:
- Online MS in Business Analytics
- Online MS in Data Analytics Engineering
- Online MS in Health Data Analytics
After completing the certificate, seamlessly apply your credits toward a master’s degree. Leverage earning your certificate while continuing into the master's program.
As an Analytics Stack Track learner, you’ll pay just $328 per credit for the certificate—significantly lowering the total cost of your master’s degree.
Current Fast App dates
Missed an enrollment deadline? Use the enrollment link in your email to enroll in the available term.
Term | Submit app by | Enroll by | Start courses |
Fall 2025 | August 1 | August 25 | September 3 |
Submit your Application by August 1 to start courses September 3.
Not ready to start?
Get more information.
Analytics Hub Fast App Pathway Courses
Explore the Fast App Performance-Based pathway courses and review the course outlines to get a head start on your preparation before classes begin.
DADS 6400: Foundations for Data Analytics Engineering
Offers topics and skills designed to prepare students for advanced courses in data analytics engineering. Covers basic concepts and implementation of methods related to probability, eigenvalues and eigenvectors, cluster analysis, text mining, and time series analysis. Offers students an opportunity to learn how to work with modern data structures and apply computational methods for data cleaning and data wrangling operations.
DADS 6600: Computation & Visualization for Analytics
Offers students an opportunity to learn how to use visualization tools and techniques for data exploration, knowledge discovery, data storytelling, and decision making in engineering, healthcare operations, manufacturing, and related applications. Covers basics of Python and R for data mining and visualization. Introduces students to static and interactive visualization charts and techniques that reveal information, patterns, interactions, and comparisons by focusing on details such as color encoding, shape selection, spatial layout, and annotation.
Get more info.
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