MS in Health Data Science - On-Campus

Dartmouth's MS in Health Data Science is offered in two formats:

• On-campus: A full-time, immersive experience in Hanover, New Hampshire, featuring in-person learning, direct faculty interaction, and access to campus resources.
• Online: Designed for working professionals, this format provides flexibility with asynchronous coursework, allowing students to complete the program remotely over 2–3 years.

Both formats lead to the same degree and cover the same rigorous curriculum. For a detailed comparison, view this chart.

Before matriculation, students may request to switch formats by emailing the Admissions office. However, after matriculation, switching is not typically allowed due to differences in structure and scheduling. In exceptional cases (e.g., personal or professional circumstances), students may request a change, though this may require transferring to a new cohort or reapplying.

Students gain hands-on experience with essential tools for healthcare data analysis, including:

• Programming Languages: Python (data analysis, machine learning), R (statistical computing), SQL (database management), SAS (clinical data analysis).
• Software & Tools: Jupyter Notebooks, RStudio, Tableau, Power BI, Hadoop, Spark (for big data processing).

While prior health data science experience is not necessary, competitive applicants typically demonstrate proficiency in data science concepts and analytical techniques. Calculus, computer programming, and statistics coursework is recommended.

Yes. Dartmouth’s program emphasizes real-world applications, offering:

• Industry-sponsored projects and case studies with healthcare organizations.
• Collaborations with faculty and industry experts through guest lectures, mentorship, and potential research or internship opportunities.
• Opportunities to work with real healthcare data to address pressing industry challenges.

Dartmouth MS in Health Data Science alumni work in biotech, pharmaceuticals, healthcare, public health, and government. Common roles include:

• Data Scientist
• Biostatistician
• Health Informatics Specialist
• Machine Learning Engineer
• Clinical Data Manager
• Public Health Analyst

Graduates use data-driven insights to improve patient outcomes, optimize healthcare operations, and inform policy decisions.

The program features a capstone project where students collaborate with industry partners or healthcare organizations to solve real-world challenges. While internships are optional, students are encouraged to gain hands-on experience through professional placements, industry-sponsored projects, and research collaborations. The on-campus program's capstone is optional and three months following the completion of the course.

This program is ideal for individuals with backgrounds in mathematics, statistics, or computer science who want to apply data science to healthcare. It suits recent graduates, working professionals, and researchers passionate about using data to solve healthcare challenges and improve patient outcomes.

The MS in Health Data Science cohort includes students from diverse fields, such as mathematics, computer science, healthcare, engineering, and public health. Many have professional experience in healthcare, data analytics, or tech, while others are transitioning into the field.

• On-campus cohort size: 30–40 students.

This is a full-time program, requiring approximately 55 hours per week of coursework and class time.

While it is possible to work while enrolled, the program’s full-time nature requires a significant time commitment. Some students manage part-time work with flexible or remote hours, but many focus on research assistantships or internships that align with their academic goals.