15 Apr, 2026Application Deadline
AugStarting Month
Programme overview
Main Subject
Public Health
Degree
MSc
Study Level
Masters
Study Mode
On Campus
Develop the skills to become a public health data scientist and improve healthcare and population health with the Public Health Data Science MS in Temple’s Christopher M. Barnett College of Public Health. This 36-credit graduate program is designed to equip graduates to meet the growing demand for data scientists who have an in-depth understanding of biostatistical methods and data analytics.
As a student, you will learn to conceptualize health problems and use state-of-the-art tools and techniques to analyze, design and manage health and health-related data to produce value-adding analytic insights. You will also learn how to effectively combine and communicate these insights to inform evidence-based public health decision-making.
Graduates of this program will have a strong biostatistical and programming foundation, a mastery of targeted data analysis, and be prepared to apply their skills as follows.
- Apply appropriate statistical methods for summarizing complex public health data, such as estimation, confidence intervals and hypothesis testing.
- Determine distinct measurement scales and recognize the implications for the selection of appropriate statistical methods.
- Distinguish statistical models with respect to data structure.
- Identify appropriate methods for data collection issues.
- Interpret and present results to professional and lay audiences.
- Recognize the concepts of probability, commonly used statistical probability distributions and random variation.
- Reveal patterns by employing efficient, fluent programming skills in conjunction with statistical inference and big data.
- Understand how experimental design influences statistical inference and uncertainty.
- Utilize appropriate machine learning algorithms that incorporate uncertainty.
Graduates of the program will also be prepared to analyze and utilize “big health data” or “complex study designs” to improve health outcomes while lowering costs, leveraging multiple data sources for infectious disease surveillance and other newly emerging issues.
Programme overview
Main Subject
Public Health
Degree
MSc
Study Level
Masters
Study Mode
On Campus
Develop the skills to become a public health data scientist and improve healthcare and population health with the Public Health Data Science MS in Temple’s Christopher M. Barnett College of Public Health. This 36-credit graduate program is designed to equip graduates to meet the growing demand for data scientists who have an in-depth understanding of biostatistical methods and data analytics.
As a student, you will learn to conceptualize health problems and use state-of-the-art tools and techniques to analyze, design and manage health and health-related data to produce value-adding analytic insights. You will also learn how to effectively combine and communicate these insights to inform evidence-based public health decision-making.
Graduates of this program will have a strong biostatistical and programming foundation, a mastery of targeted data analysis, and be prepared to apply their skills as follows.
- Apply appropriate statistical methods for summarizing complex public health data, such as estimation, confidence intervals and hypothesis testing.
- Determine distinct measurement scales and recognize the implications for the selection of appropriate statistical methods.
- Distinguish statistical models with respect to data structure.
- Identify appropriate methods for data collection issues.
- Interpret and present results to professional and lay audiences.
- Recognize the concepts of probability, commonly used statistical probability distributions and random variation.
- Reveal patterns by employing efficient, fluent programming skills in conjunction with statistical inference and big data.
- Understand how experimental design influences statistical inference and uncertainty.
- Utilize appropriate machine learning algorithms that incorporate uncertainty.
Graduates of the program will also be prepared to analyze and utilize “big health data” or “complex study designs” to improve health outcomes while lowering costs, leveraging multiple data sources for infectious disease surveillance and other newly emerging issues.
Admission Requirements
- Candidates are required to submit references or letter(s) of recommendation for acceptance
Scholarships
Selecting the right scholarship can be a daunting process. With countless options available, students often find themselves overwhelmed and confused. The decision can be especially stressful for those facing financial constraints or pursuing specific academic or career goals.
To help students navigate this challenging process, we recommend the following articles:
How to get a full scholarship
Looking for a fully-funded scholarship to see you into university? Find out how to boost your chances of getting one.
Scholarships to study abroad
Find scholarships to study abroad with our lists of international scholarships – categorized by country, by subject, and by type of student.
Scholarship Applications: Frequently Asked Questions
Get answers to all your questions about scholarship applications, including tips on how to find scholarships and chances of success.
Get closer to your dream programme
Your consent preferences have been set.
Time to start exploring.
Your account has been removed.
You can still browse the site or sign up again once you have parental consent.
Get closer to your dream programme